Session Descriptions

Please scroll down to review the full set of proposed sessions or click on a title to jump directly to a specific description. Round table proposals are posted on a separate round table page.

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S1: Chronological modelling II: formal methods and research software

Session Organisers:
Eythan Levy, University of Zurich
Thomas Huet, University of Oxford

Description

Session Format: Standard

Time and its analysis are at the heart of archaeology: one of the main objectives of the archaeologist is the establishment of a temporal framework for a given layer, site or material culture. But archaeology covers such a wide range of cultures, dispersed both in time and space, that contextual chronological assessments are constructed using very different tools, languages and techniques. It creates as many different temporal and cultural frameworks as there are specialties, with notable differences in approaches depending on whether one is dealing with absolute or relative chronology, laboratory techniques or cultural approaches, deterministic or statistical methods (Buck and Millard 2004).

The principle of a Special Interest Group (SIG) on chronological modelling (SIG-CHRONO) has been approved by the CAA steering committee during the 2024 Annual General Meeting (AGM), and a formal proposal for its creation will be presented at the 2025 CAA conference. The proposed session will be related to this new SIG, in order to explore a wide variety of research tools and techniques related to (semantic) chronological modelling in archaeology and to identify common methodological frameworks and to build bridges between specialties.

We strongly encourage submissions presenting new mathematical models and algorithms for handling  chronological data, whether based on deterministic or probabilistic approaches (e.g., Bayesian methods, stratigraphic modelling, temporal logics; see: https://github.com/historical-time/caa-chrono-sig/tree/main/doc). Additionally, we welcome contributions focused on open-source and open-access software. Papers addressing interoperability between different chronological models (or their implementations) are also encouraged. This includes topics such as the use of ontologies (e.g., CRMarchaeo, SKOS), controlled vocabularies and time gazetteers (e.g., PeriodO, ChronOntology), and the application of ISO standards like Date and EDTF, in the framework of Linked Open Data.

Reference

Buck, C.E. and Millard, A. 2004. Tools for Constructing Chronologies: Crossing Disciplinary Boundaries. London.

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S2: Future-Proof Heritage: AI, Digital Twins, and Sustainable Preservation

Session Organisers:
George Pavlidis, Athena Research Center
Anestis Koutsoudis, Athena Research Center

Description

Session Format: Standard

In the face of growing environmental challenges, the need for advanced strategies to preserve cultural heritage is more urgent than ever. Artificial Intelligence and digital twin technologies can have a transformative potential for safeguarding cultural heritage, particularly in remote and vulnerable locations. A digital twin [1-5] is a dynamic digital replica of a physical structure that integrates diverse data sources such as geometric, spectral, geographic, remote sensing, and environmental data. By leveraging multimodal and multi-dimensional information, digital twins provide an enriched understanding of heritage sites, enabling holistic monitoring, predictive analysis, and effective risk management.

In this session, we will discuss how digital twins are being used in this context, incorporating real-time monitoring and supporting sustainable preservation through risk assessment and scenario modeling. The discussion may place emphasis on integrating satellite data, climate information, and conservation records to assess the impact of environmental and anthropogenic factors on heritage sites. Through advanced AI methodologies, including threat identification, content analysis, novelty or defect detection, and multimodal monitoring, digital twins can offer a comprehensive strategy for preventive conservation and sustainable heritage management.

Key topics include:

  • Digital Twins for Heritage: Development and implementation of models supporting multi-modal data integration.
  • Advanced Digitization: Techniques enhancing the accuracy and detail of digital representations of heritage sites.
  • Non-destructive and Multimodal Monitoring: Innovations in portable systems using miniaturized sensors for comprehensive physical, chemical, and content analysis.
  • AI for Threat Identification and Novelty Detection: AI-driven approaches to predict and mitigate environmental and human-induced risks to heritage assets.
  • Data Fusion: Combining diverse data sources for a holistic view of heritage site conditions and challenges.
  • Decision Support Systems: Trustworthy AI tools for preventive preservation, enabling proactive damage prevention.

This session is intended for researchers, heritage managers, and practitioners, offering insights into the latest advancements that can transform heritage management and ensure the longevity of cultural assets.

References

[1] Pantoja-Rosero, B.G., Achanta, R., Kozinski, M., Fua, P., Perez-Cruz, F., Beyer, K. (2022). Generating LOD3 building models from structure-from-motion and semantic segmentation. Automation in Construction, 141, 104430.

[2] Grieves, M. (2014). Digital Twin: Manufacturing Excellence through Virtual Factory Replication. (A foundational work introducing the concept of digital twins and its applicability to asset management.)

[3] Stratis, J.A, Makarona, C, Lazidou, D, Sánchez, E.G, Koutsoudis, A, Pamplona, M, Pauswein, R, Pavlidis, G, Simon, S, Tsirliganis, N. (2014). Enhancing the examination workflow for Byzantine icons: Implementation of information technology tools in a traditional context. Journal of Cultural Heritage, 15(1), 85-91.

[4] Arnaoutoglou, F., Evagelidis, V., Pavlidis, G., Tsirliganis, N., & Chamzas, C. (2003). 3D-GIS: New ways in digitization and visualization of cultural objects. In Workshop on the Digitization of Cultural Content (Vol. 27, p. 28).

[5] Tsirliganis, N, Pavlidis, G, Koutsoudis, A, Papadopoulou, D, Tsompanopoulos, A, Stavroglou, K, Loukou, Z, Chamzas, C. (2002, June). Archiving 3D cultural objects with surface point-wise database information. Proc..1st International Symp. on 3D Data Processing Visualization and Transmission (pp. 766-769). IEEE.

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S3: Innovating Archaeological Exploration: AI-based approaches to Remote Sensing

Session Organisers: Argyro Argyrou, Cyprus University of Technology (chair)
Nejc Čož, ZRC SAZU (chair)
Steve Wernke, Vanderbilt University (chair)
Parker VanValkenburgh, Brown University (chair)
James Zimmer-Dauphinee, Vanderbilt University (chair)
Axel G. Posluschny, Keltenwelt am Glauberg – Research Centre
Susan Curran, Discovery Programme
Žiga Kokalj, ZRC SAZU
Athos Agapiou, Cyprus University of Technology, Deputy Director of UNESCO Chair on Digital Cultural Heritage

Description

Session Format: Standard

The vastness of the archaeological record presents significant challenges for both documentation and conservation. Remote sensing data and products are increasingly integrated into archaeological science and cultural heritage research. It offers a non-destructive approach to efficiently search and map ACH sites at various scales, analyze multiple data sets, and monitor sites and their surroundings (Argyrou & Agapiou, 2022). A growing body of scientific literature showcases numerous successful applications, demonstrating the significant impact of this technology (Agapiou & Lysandrou, 2015; Tapete & Cigna, 2019; Luo et al, 2019; Somrak et al., 2020; Verschoof-van der Vaart et al., 2021; Guyot et al., 2021).

Remote data collection is vital for both purposes, because it facilitates our work at larger scales, allowing us to collect systematic data that span regions, while also identifying conservation risks and priorities. However, the scales of remote sensing datasets themselves can also serve as an impediment to efficient processing and analysis. The rapid advancement of various deep learning models (convolutional neural networks and vision transformer frameworks principle among them) opens up new possibilities for expanding and intensifying the scale and efficiency of archaeological data processing. However, AI models create their own challenges. Most models trained to detect features in “natural images” (photos of objects in the ambient environment) must be fine-tuned to detect archaeological features, requiring large databases of known and recorded features. Nevertheless, due to the sparseness of archaeological data, model sensitivity and specificity remain challenging in such approaches. Manually auditing the results of AI surveys presents its own challenges, due to the sheer volume of AI-derived feature detections.

This session welcomes submissions from scholars who are employing AI models to process and analyse remote sensing data, including high-resolution satellite imagery, low-altitude (low-cost) sensors and airborne laser scanning (ALS). Contributions from all regions of the world and time periods are welcome. Research-focused and heritage documentation and management orientations are both welcomed. Projects at various stages are also welcome, as are both analytical reports of AI-based survey results, and methods-focused contributions. Our themes include:

  • Foundation Models: Deep learning frameworks use foundation models as the basis for visual and semantic features for downstream tasks. How have domain-specific foundation models impacted fine-tuning and model performance?
  • Training Data: Training machine learning models requires large amounts of high-quality annotated data. This involves acquiring and pre-processing remote sensing data, creating annotation data, and implementing quality control measures to reduce bias.
  • Data Quality: Topographic data from diverse sources varies in accuracy. How can we ensure high-quality, consistent data for accurate model training and implementation?
  • Data Processing: What are the best approaches to pre-process and visualise data for training machine learning models and deep learning methods?
  • MLM Development: Selecting ML models (U-Net, HRNet, DeepLab, etc.) and methodologies (image classification, semantic segmentation, object detection) for various archaeological sites. Is it possible the same ML and DL methods be used for different data types?
  • Challenges of applying MLMs developed in one region to another, benefits of retraining with new data (transfer learning), and strategies for addressing domain adaptation issues.
  • MLM Evaluation: What level of false positives are observed in current ML tools, and what factors contribute to these errors? How is the accuracy of the MLM measured? How can we design efficient workflows for human verification of detections, especially when dealing with large data sets? How can additional geospatial information support this process?
  • What software tools are available for archaeologists to incorporate MLMs into their research, and what new tools should be developed? How should these tools be integrated into current workflows, and what should the standard outputs look like?
  • Open Software & Data: How can we make ML software tools open for further development while remaining accessible to novices? How can we ensure FAIR and sustainable analysis and classification of remote sensing data using semi-automated workflows?

As the field is still in an “early adopter” phase of AI-based methodologies, empirical findings-substantial and growing as they are-remain at the low end of what promises to be a steep and tall curve of data outputs from AI-based imagery survey projects. Methodological advances and challenges in AI are also matters of ongoing concern in this emergent and rapidly developing computational field. Thus, the primary goal of this session is to provide a platform for participants to report on results and emerging methods, algorithms, code, APIs, and workflows. This will allow for a thorough exploration of different approaches and their potential applications. Through this session we hope to provide a forum for researchers already working on these topics with the aim of further developing a community of research specialists using AI for cultural heritage preservation, identifying benefits, and exploring challenges and limitations. In doing so, we hope to encourage others to create their own ML models and aid further development of ML remote sensing tools and potential in archaeology.

References

Argyrou, A.; Agapiou, A. A Review of Artificial Intelligence and Remote Sensing for Archaeological Research. Remote Sens. 2022, 14, 6000.

Agapiou, A., Lysandrou, V. Remote sensing archaeology: Tracking and mapping evolution in European scientific literature 992 from 1999 to 2015. Journal of Archaeological Science, 2015, 4, 192–200

Tapete, D.; Cigna, F. Detection of Archaeological Looting from Space: Methods, Achievements and Challenges. Remote Sens. 2019, 11(20), 2389.

Luo, L.; Wang, X.; Guo, H.; Lasaponara, R.; Zong, X.; Masini, N.; Wang, G.; Shia, P.; Khatteli, H.; Chen, F.; et al. Airborne and spaceborne remote sensing for archaeological and cultural heritage applications: A review of the century (1907–2017). Remote Sens. Environ. 2019, 232, 111280.

Eppelbaum, L. V., Khabarova, O., Birkenfeld M., Advancing archaeo-geophysics through integrated informational-probabilistic techniques and remote sensing, Journal of Applied Geophysics 227 (2024) 105437

Guyot, Alexandre, Marc Lennon, and Laurence Hubert-Moy. 2021. ‘Objective Comparison of Relief Visualisation Techniques with Deep CNN for Archaeology’. Journal of Archaeological Science: Reports 38:103027. https://doi.org/10.1016/j.jasrep.2021.103027.

Somrak, Maja, Sašo Džeroski, and Žiga Kokalj. 2020. ‘Learning to Classify Structures in ALS-Derived Visualizations of Ancient Maya Settlements with CNN’. Remote Sensing 12 (14): 2215. https://doi.org/10.3390/rs12142215.

Verschoof-van der Vaart, Wouter B., and Juergen Landauer. 2021. ‘Using CarcassonNet to Automatically Detect and Trace Hollow Roads in LiDAR Data from the Netherlands’. Journal of Cultural Heritage 47 (January): 143-54. https://doi.org/10.1016/j.culher.2020.10.

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S4: Hic sunt dracones! Semantics and archaeological Linked Open Data within the FAIRification process and Research Data Lifecycle along the Object Biography

Session Organisers:
Florian Thiery, Leibniz-Zentrum für Archäologie (LEIZA)
Karsten Tolle, Goethe University
Ethan Gruber, American Numismatic Society
Daria Stefan, TU Wien

Description

Session Format: Standard

In historical maps, the phrase “Hic sunt dracones” (engl. ~here be dragons) is used to describe areas which were unknown to the map creator. Today, the WWW offers researchers the possibility of sharing their research (data), enabling the community to participate in scientific discourse and create new knowledge. However, much of this shared data is not findable or accessible, thus resulting in modern ‘unknown data dragons’. Often, these ‘data dragons’ lack connections to other datasets, i.e., they are not interoperable and, in some cases, also lack usability. To overcome these shortcomings, Linked Open Data (LOD) techniques can be used. In 2006, Berners-Lee introduced the concept of LOD; in 2018 Sanderson instigated the “Usable” aspect at EuropeanaTech. In 2016, the FAIR principles were introduced: Findable, Accessible, Interoperable and Reusable. Semantic Modelling and Linked Open (Usable) Data are a huge part of Computational Archaeology and also an important part of the FAIRification and Research Data Management (RDM) process inside the Research Data Lifecycle and along the digital object biography 5-7. These results in interconnected Linked Open Data to reach Open Science and play a huge role in international and interdisciplinary RDM initiatives such as the German National Research Data Infrastructure (NFDI) and its archaeology-related consortium NFDI4 Objects 8 and the European Open Science Cloud (EOSC) 9 . The Semantic Web offers a variety of vocabularies, ontologies and reference models that can be used for archaeology-related LOD modelling: CIDOC-CRM, SKOS, PROV-O, FOAF, GeoSPARQL, Wikidata, etc. The Linked Data Cloud already provides FAIR and LOUD research data repositories, data hubs and domain-specific ontologies for specific archaeological and humanities domains such as Nomisma, Kerameikos, Pelagios, OpenContext, Portable Antiquities Scheme, ARIADNE, Linked Open Samian Ware, Linked Open ARS, Linked Open Ogham, and the Ceramic Typologies Ontology. To enable non-experts to engage with FAIR and LOUD data, research tools – little minions – were created for different purposes, such as modelling relative chronologies in RDF, modelling and reasoning on vague edges in graph data, creating annotated texts and images, and SPARQL, as well as enhancing Geo-Datasets using, i.e., the SPARQLing Unicorn QGIS Plugin. In addition, community-driven knowledge bases like Wikidata not only offer data but also provide a number of tools for using and interacting. Our session aims to bring together experts and colleagues interested in learning about FAIR and LOUD data-driven publishing and applications and collecting research application scenarios to jointly promote research domain-specific solutions for research data management. We would like to discuss application-oriented and data-driven investigations into improving technologies for FAIR and LOUD data models as a basis for reproducible and CAREful research and exchange on the Semantic Web, as well as solutions related to one or more of the issues listed below:

  • application of Semantic Web technologies, such as ontologies (e.g. CIDOC-CRM) or RDF, to the archaeological domain
  • modelling of archaeological artefacts, the archaeological context, including the specificity of stratigraphy, uncertainty, and vagueness
  • development of research tools producing or using FAIR and LOUD data
  • identifying sources and dangers of incorrect or ambiguous LOD, e.g., duplicates across different LOD sources
  • keeping track of the provenance of data as a means of solving errors and identifying their source
  • setting up research-question-based methodologies and tools to label or assess datasets based on their quality
  • dealing with ambiguities resulting from multiple links in the LOD cloud
  • computer vision or machine learning applications built upon controlled semantic data
  • building up Knowledge Graphs by applying semantic and Artificial Intelligence (AI) technologies
  • modelling comprehensible/reproducible workflows and data flows using RDF for documentation and reproducible research
  • use of Linked Open Data related tools in archaeological research, their implementation and/or enhancement
  • possibilities, challenges, benefits and risks of the Wikimedia Universe (e.g. Wikidata, Wikibase instances, Wikimedia Commons) in archaeological research
  • implementation of reference models such as CIDOC-CRM in real-world datasets and ways to achieve LOD
  • graphs of facts, beliefs, and/or assertions as a digital archaeological method
  • reasoning with heterogeneous and real-world archaeological data in graphs
  • granularity in LOD/graphs/networks
  • graph and RDF representation of specific networks of persons, objects and information relating to research questions
  • interacting with graphs and graph interaction design
  • LOUD techniques as a solution for information and data annotation on objects/artefacts in 2D and 3D (e.g. cuneiform tablets, ogham stones, samian ware, books, texts, …)
  • semantically modelling geospatial data FAIR and LOUD
  • implementation of GeoSPARQL as a geospatial standard in archaeological data
  • things as a concept, such as places (e.g. Pleiades Place/Location), persons (e.g. “potters” as Actors) and events in archaeological LOD
  • overcoming linguistic barriers and increasing accessibility through LOD
  • implementing the CARE principles through thoughtful LOD application
  • development of educational or Open Educational Resources (OERs) to increase the use of LOD

We encourage presenters to derive the problems addressed from real-world datasets and to formulate proposals for solutions, preferably demonstrating (prototypes of) realised data-driven (web-) applications. Due to the thematic relevance, we target a broad and diverse audience, and the challenges described should also be integrated into an archaeological context (excavation, museum, archive, etc.). This session is organised by the CAA SIG on Semantics and LOUD in Archaeology (SIG Data-Dragon). The core aim of this SIG is to use the SIG format to raise awareness for Linked Data in archaeology by creating a friendly and open platform to discuss and further develop semantics and LOUD and FAIR data in archaeology.

References

[1] Hylandet et al. (2013). URL: https://www.w3.org/TR/ld-glossary/.

[2] Berners-Lee. (2006). URL: https://www.w3.org/DesignIssues/LinkedData.html.

[3] Sanderson (2018). URL: https://de.slideshare.net/Europeana/shout-it-out-loud-by-rob-sanderson-europeanatech-conference-2018-98225909.

[4] Wilkinson et al. (2016). DOI: 10.1038/sdata.2016.18.

[5] Thiery et al. (2023). DOI: 10.52825/cordi.v1i.326.

[6] Schmidt, Thiery & Trognitz (2022). DOI: 10.3390/digital2030019.

[7] Thiery et al. (2023). DOI: 10.3390/ijgi12040167.

[8] Thiery & Schubert (2023). DOI: 10.5281/zenodo.10112836.

[9] Budroni, Claude-Burgelman & Schouppe (2019). DOI: 10.1515/abitech-2019-2006.

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S5: Our Little Minions pt. VI: small tools with major impact

Session Organisers:
Ronald Visser, Saxion University of Applied Sciences
Florian Thiery, Leibniz-Zentrum für Archäologie (LEIZA)
Brigit Danthine, Austrian Archaeological Institute (Austrian Academy of Science)
Lutz Schubert, University of Cologne

Description

Session Format: Other

In our daily work, small self-made scripts (e.g. Python or R), home-grown small applications (e.g. QGIS Plugins) and small hardware devices significantly help us to get work done. These little helpers -“little minions” – often reduce our workload or optimise our workflows, although they are not often presented to the outside world and the research community 1 . Instead, we generally focus on presenting the results of our research and silently use our small tools during our research without even pointing to them, especially not to the source code or building instructions. This session will focus on these small helpers – “little minions” – and we invite researchers to share their tools so that the scientific community may benefit. As we have seen in last year’s “minion talks” since 2018 there is a wide range of tools to be shared. The Little Minion software tools have evolved from their niche existence into important components of projects and consortia. They are a huge part of the archaeological Research Software Engineering community (also Computational Archaeology) and also an important part of the Research Data Management (RDM) process inside the Research Data Lifecycle and the digital object biography 2 . This can result in, i.e., FAIRification Tools 3-6 (Findable, Accessible, Interoperable, Re-Usable) [5] and research tools for reproducible quantitative/spatial analysis. These results play a huge role in international and interdisciplinary initiatives such as the German National Research Data Infrastructure (NFDI) and its archaeology-related consortium NFDI4Objects 7 as well as the Community Cluster / Working Group Research Software Engineering 8,9 or the European Open Science Cloud (EOSC) 10 . This already sixth Little Minion session invites short presentations, lightning talks (max. 7-10 minutes including very short discussion) – of small coding pieces, software or hardware solutions in any status of completion, not only focusing on fieldwork or excavation technology, associated evaluation or methodical approaches in archaeology. Each talk should explain the innovative character and mode of operation of the digital tool. The only restriction is that the software, source code and/or building instructions are open and are or will be freely available. Proprietary products cannot be presented, but open and freely available tools are designed for them. To support the subsequent use of the tools, the goal should be to make them open and available to the scientific community (e.g., GitHub, GitLab). We invite speakers to submit a short abstract including an introduction to the research tool, the link to the repository – if possible – to access the source code and an explanation of which group of researchers could benefit from the little minion and how. The tools may address the following issues but are not limited to (you will find an overview of the previous sessions under https://littleminions.link)

  • data processing tools and algorithms
  • measuring tools
  • digital documentation tools
  • GIS plugins
  • hands-on digital inventions (e.g. for excavations)
  • data-driven tools (e.g. Linked Data, CSV, Big Data) 

After previous years’ spontaneous success of “Stand-up-Science”, you will also have the opportunity to spontaneously participate and demonstrate what you have on your stick or laptop. If you want to participate without an abstract in the spontaneous section of the session, don’t hesitate. Please come and spontaneously introduce your little minion! The minion session is designed for interested researchers of all domains who want to present their small minions with a focus on the technical domain and also for researchers who want to get ideas about what kinds of little minions are available to help with their own research questions. All of us use minions in our daily work, and often tools for the same task are built multiple times. This online session gives these tools that are considered too unimportant to be presented in normal talks, but take important and extensive steps in our research, a home. As an outcome of the session, we try to give support, that all presented tools and links to code repositories will be available for the research community on our website https://littleminions.link.

Other Format Description

This is (would be) the sixth session on these little helpers with the same format: short lightning talks (max. 7-10 minutes including very short discussion). We would like also have the idea of \Stand-up-Science\”. Participants should have the opportunity to spontaneously participate and demonstrate what they have on your stick or laptop. So we would need some more time to have some spontaneous talks.”

References

 [1] Thiery, Visser & Mennega (2021). DOI: 10.5281/zenodo.4575167.

[2] Thiery et al. (2023). DOI: 10.52825/cordi.v1i.326.

[3] Thiery, Schubert & Fricke (2024). DOI: 10.5281/zenodo.10774878.

[4] Thiery & Homburg (2024). DOI: 10.5281/zenodo.10790939.

[5] Fricke & Thiery (2024). DOI: 10.5281/zenodo.10756823.

[6] Wilkinson et al. (2016). DOI: 10.1038/sdata.2016.18.

[7] Bibby et al. (2023). DOI: 10.5281/zenodo.10409227.

[8] Thiery & Flemisch (2024). DOI: 10.5281/zenodo.10805071.

[9] Thiery & Schubert (2023). DOI: 10.5281/zenodo.10112836.

[10] Budroni, Claude-Burgelman & Schouppe (2019). DOI: 10.1515/abitech-2019-2006.

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S6: Model-Driven Urban Archaeology

Session Organisers:
Philip Verhagen, Vrije Universiteit Amsterdam
Iza Romanowska, University of Aarhus
Dries Daems, Vrije Universiteit Amsterdam

Session Format: Standard

Description

Archaeology is increasingly pursuing computational modelling as a tool to reconstruct and interpret past human behaviour. The combination of spatial, statistical and network analytical techniques applied to ever larger datasets and employing increased computing power, has now opened up opportunities for exploring the human past at an unprecedented range of spatial and temporal scales. Agent-based modelling studies have tackled topics such as settlement system dynamics, subsistence production, socio-economic relations and population development in many case studies around the world. Least-cost path modelling is increasingly applied to a wide range of studies to better understand movement and transport. Statistical simulations are used to estimate, among others, the chronology of settlements and finds, the spatio-temporal distribution of settlements and the density of population. Network analysis is applied to reconstruct the exchange of goods and people, to understand human-animal relationships and to analyse the spatial configuration of sites and route networks, to name just a few. So far, the use of computational modelling in urban contexts has somewhat lagged behind. Urban archaeology is a data-heavy discipline in which ‘clean’, easy-to-interpret data are the exception rather than the rule, given that many urban contexts have long occupation histories that sometimes span millennia and are densely packed with archaeological remains. Also, ‘urban’ and ‘non-urban’ contexts are seldom studied in conjunction, providing a challenge to understanding urban-hinterland interactions. The general complexity of urban archaeology makes it a fertile ground for the application of data science and computational modelling approaches to solve archaeological research questions. In this session, we invite papers that showcase applications of computational modelling in urban archaeology contexts, and that reflect on the potential and limitations of these methods for increasing our understanding of topics such as population dynamics, movement and transport, socio-economic interactions and urban-hinterland relationships. Case studies can include, but are not limited to, single urban settlements, regional studies or supra-regional, comparative studies. We also welcome methodological papers focused on solving problems specific to urban datasets and research questions.

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S7: Cognitive Mind

Session Organisers:
Fujita Haruhiro, Niigata University of International and Information Studies
Kawano Kazutaka, Tokyo National Museum
Yamamoto Ryo, Tokyo National Museum
Miyao Toru, Niigata Prefecture History Museum

Description

Session Format: Standard

Academic Background

The Mind, capable of abstract thinking, is considered a distinctive feature of modern humans, Homo sapiens.  Archaeological evidence includes ornaments such as shell beads found in the Skhul Cave in Israel, which may date back to around 100,000 years, as well as the cave paintings of Lascaux in France and Altamira in Spain.  Additionally, Paleolithic figurines such as the Lion Man and Venus figurines are widely known across Europe and the Eurasian continent.  While no cave paintings have been discovered from the Paleolithic or Jomon periods of the Japanese archipelago, artifacts believed to be stone and clay figures and ornaments have been found, suggesting they are part of a group of Homo sapiens that dispersed across the globe.  Notably, Jomon clay figures, known as Dogu, a general term for human-shaped clay products, were consistently present throughout the Jomon period, albeit in varying quantities, but dramatically declined and disappeared during the Yayoi period.  Therefore, Dogu can be considered artifacts that narrate the unique cognitive mind of the Jomon period. Methods to extract and distinguish the relationship between these stylistic characteristics and the mind, or the commonality and continuity of these characteristics within and beyond regions in the same community (site), are now being investigated as follows.

Commonalities of cognitive processes and mind structures

“Cognitive Archaeology, Body Cognition and Evolution of Visuospatial Perception” (2023) [2] illustrated how body perception and spatial sensing might have evolved in humans, which suggests both body perception and spatial sensing have commonalities among human beings. Matsumoto (2000) [3] used the theory and methods of cognitive archaeology to argue that the mind and body have had developed together in the course of human evolution, and therefore the structure of the mind should be considered to be common to the same extent as the structure of the human body.  She also claimed that there was a certain degree of universality in human cognitive processes and cognitive structures, and that the same models and conceptual frameworks could be applied across differences in culture and social structure.

VR and MR from instant 3D view to gaze heatmap experiment

 VR (Virtual Reality) and MR (Mixed Reality) represented a significant advancement by enabling viewers to see and simulate things that are not normally visible.  Artifacts converted to 3D can be easily visible by VR/MR equipment, therefore one can obtain instant experience of viewing ancient artifacts. Apple Vision Pro is capable of capturing the viewer’s gaze data using its built-in cameras and sensors. This data includes the 3D coordinates of the fixation point, the direction of the gaze, and the fixation duration (saccades and fixations), serving as indicators of where a person’s potential mind is directed on an object. By projecting the duration of gaze fixation on the surface of the object as color-graded information, it can be visualized as a 3D heatmap.

Measuring Cognitive Mind and Gaze Heatmap Using SD Method and Eye Tracking

As an experimental method for extracting the mental images people have when viewing objects, the Semantic Differential (SD) method is widely used in psychological testing.  This method involves providing pairs of simple sensory impression adjectives, such as “beautiful-ugly,” for subjects to rate on a scale.  The SD method serves as crucial information to analyze how people perceive objects as stimuli through many simple sensory impression adjectives. A research paper using this method is currently under peer review at DOI/PCI Archaeology. The Apple Vision Pro can capture viewers’ gaze data and 3D gaze heatmap can be produced as mentioned previously.

Reconstructing the Mind Using Deep Mind Generative Models

 After a long period of stagnation, machine learning experienced a major turning point with deep learning for image recognition in 2012.  Over the past 12 years, advancements in deep learning models have led to cognitive and mind analysis capabilities far exceeding human abilities.  Recently, these models have been applied to mind analysis as part of information psychology.  By analyzing sensory impressions of subjects viewing artifacts along with data on these objects, deep mind models offer new insights.

The Need for Cognitive Mind Sessions

Cognitive archaeology, deeply intertwined with experimental psychology and cognitive information processing, is a crucial field for exploring human psychology and the mind through archaeological artifacts and sites.  However, aside from the presentation proposed by the authors (currently under review) at CAA2024, no relevant research was identified.   While it is impossible to directly investigate the mind of ancient people, it is considered feasible to reconstruct their cognition and mental images under the assumption of commonality with modern human cognition, which were proposed by Burner and Matsumoto.  Therefore, a group centered around the Archaeological Cultural Heritage Deep Learning Research Association proposes holding a Cognitive Mind Session.

Possible investigations and methodologies:

  • 3D views of artifacts by VR/MR equipment and investigations on observers’ perception
  • VR/MR practices for historical and regional education
  • VR/MR exhibition as digital museum
  • Eye tracking and gaze heatmap methodologies for cognitive investigations
  • Any cognitive mind related investigations and methodologies
  • Deep mind investigations using cognitive data and deep learning models

References

Fujita: A paper of sensory impression factor structures of Jomon potteries through a MR experiment presented at CAA2024,under review. https://doi.org/10.5281/zenodo.13846760

Bruner, E., 2023. Cognitive Archaeology, Body Cognition, and the Evolution of Visuospatial Perception. Elsevier Science & Technology, San Diego, UNITED STATES

Matsumoto Naoko 2000. Theory and practice of cognitive archaeology. Measuring Mental Images

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S8: Digital lifescapes: using multi-scalar approaches to map, model and reimagine urbanism, settlement and landscapes in archaeology

Session Organisers:
Lawrence Shaw, Forestry England
Derek Pitman, Bournemouth University
Rich Potter, University of Gothenburg
Josie Hagan, Insitu Heritage

Description

Session Format: Standard

The last few decades have witnessed a significant global uptake in accessible digital approaches to recording (Hill et al., 2019), re-constructing and visualising archaeological data and remains from multiple periods. From landscape scale born-digital datasets (Hill, 2019) including geophysical survey, lidar and other digital mapping approaches (Potter et al., 2023), to GIS (Dell’Unto and Landeschi, 2022) and game engine technology there has never been more data produced and shared with the aim of understanding human activity. Notably, approaches have given life to studies that explore the interplay between multiple scales of digital data and the interpretation of past practice. Similarly, approaches that visualise and re-imagine archaeological remains in novel and accessible ways have become increasingly accessible and widely applied. This session aims to celebrate these developments and ask ‘how can the digital pioneers of data collection and interpretation work together to capture and share the rich variety inhabitation and exploitation within complex and dynamic landscapes?’. Most notably, we are interested to see examples of the application of multi-scalar approaches to inform the development of urbanism with past landscapes. Papers are welcomed from practitioners across the spectrum from those engaged in fieldwork to those digital artists who bring the past to life. The session hopes to stimulate discussion around the use of archaeological data in interpretation workflows and develop a clear trajectory between data collected in the field and data reimagined within digital environments. We would also encourage papers that demonstrate scalability of research from artefacts, structures, settlement, and landscape, and how this scalability has informed academic research and public engagement in similarly multi-faceted manners.

References

Dell’Unto, N. & Landeschi, G., 2022. Archaeological 3D GIS. Routledge. Available at: https://library.oapen.org/handle/20.500.12657/52629 (Accessed: 4 September 2024).

 Hill, A.C., 2019. Economical drone mapping for archaeology: Comparisons of efficiency and accuracy. Journal of Archaeological Science: Reports, 24, pp.80-91.

Hill, A.C., Limp, F., Casana, J., Laugier, E.J. and Williamson, M., 2019. A new era in spatial data recording: Low cost GNSS. Advances in Archaeological Practice, 7(2), pp.169-177.

Potter, R., Pitman, D., Manley, H. et al. Cost-effective, rapid decorrelation stretching and responsive UAS mapping as a method of detecting archaeological sites and features. Herit Sci 11, 89 (2023). https://doi.org/10.1186/s40494-023-00931-6.

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S9: Pixels in Training: Image-Based Machine Learning Applications in Archaeology

Session Organisers:
Anastasia Eleftheriadou, ICArEHB, University of Algarve
Amy Hatton, Max Planck Institute of Geoanthropology
Sofia Kouki, ICArEHB, University of Algarve
Mathias Bellat, University of Tübingen

Description

Session Format: Standard

Session Overview

In the rapidly evolving field of archaeology, machine learning (ML) has introduced new lines of research, particularly in the area of image analysis. Archaeologists have used machine learning for the classification and segmentation of images across different scales and features. One of the most common applications involves identifying near-surface features in the landscape, such as structures and tells, through satellite imagery (Menze and Ur 2012; Orengo et al. 2020). However, the range of images analyzed in archaeology using machine learning has expanded significantly in recent years to include data from a variety of sources. Drone photography has been used to identify artifacts (Orengo et al. 2021) and structures (Monna et al. 2020). Images acquired with personal cameras are primarily used for the classification of artifacts (Santos et al. 2024; Zhao et al. 2023). Microscopic images have recently been integrated into machine learning applications across various fields, including geoarchaeology (Zickel et al. 2024), use-wear analysis (Luncz et al. 2022), physical anthropology (Tanti et al. 2021), and taphonomy (Courtenay et al. 2020).

Session Aim

This session aims to explore recent advancements, current challenges, and future prospects in the application of image-based machine learning in archaeology. Key topics for discussion may include:

  1. Data Acquisition:
    1. Strategies for bridging the gap between specialists who acquire image data and researchers who develop machine learning models.
    1. Best practices for managing and sharing archaeological image data, including considerations for systematic data acquisition and reproducibility (Wilkinson et al. 2016).
    1. Explore the potential of crowdsourcing and citizen science for creating and annotating large datasets.
    1. Evaluate how the physical properties of materials (such as lithics, glass, pottery, metal and sedimentology) affect image quality and analysis.
  2. Data Analysis:
    1. Common challenges and pitfalls in using images as inputs for ML models.
    1. Learning with noisy labels and limited data: managing data scarcity and inconsistencies in image quality.
    1. Developing coherent workflows that are appropriately aligned with the data and research questions (Fayyad, Piatetsky‐Shapiro and Smyth 1996).
Call for Papers

We invite submissions that investigate the application of machine learning in archaeological research using imagery, addressing various scales, materials, and time periods. Potential contributions may include, but are not limited to:

  1. Supervised/unsupervised/semi-supervised algorithms, transfer learning, deep learning.
  2. Feature extraction, segmentation, classification.
  3. Pattern recognition and analysis, computer vision, image restoration.
  4. Physical anthropology, zooarchaeology, use-wear analysis, geoarchaeology, remote sensing.

In this session, we focus on dialogue, exchange of ideas, and constructive feedback. Consequently, we will ensure there is ample time available for this purpose.

References

Courtenay, LA, Huguet, R, González-Aguilera, D and Yravedra, J. 2020 A hybrid geometric morphometric deep learning approach for cut and trampling mark classification. Applied sciences 10(1): 150-. DOI: https://doi.org/10.3390/app10010150.

Fayyad, U, Piatetsky‐Shapiro, G and Smyth, P. 1996 From data mining to knowledge discovery in databases. The AI magazine 17(3): 37–54.

Luncz, LV, Braun, DR, Marreiros, J, Bamford, M, Zeng, C, Pacome, SS, Junghenn, P, Buckley, Z, Yao, X and Carvalho, S. 2022 Chimpanzee wooden tool analysis advances the identification of percussive technology. iScience 25(11): 105315–105315.

Menze, BH and Ur, JA. 2012 Mapping patterns of long-term settlement in Northern Mesopotamia at a large scale. Proceedings of the National Academy of Sciences – PNAS 109(14): E778–E787.

Monna, F, Magail, J, Rolland, T, Navarro, N, Wilczek, J, Gantulga, J-O, Esin, Y, Granjon, L, Allard, A-C and Chateau-Smith, C. 2020 Machine learning for rapid mapping of archaeological structures made of dry stones – Example of burial monuments from the Khirgisuur culture, Mongolia. Journal of cultural heritage 43: 118–128.

Orengo, H, Berganzo-Besga, I, Landauer, J, Aliende, P, Tres-Martínez, S and Garcia-Molsosa, A. 2021 New developments in drone-based automated surface survey: Towards a functional and effective survey system. Archaeological Prospection 28: 1–8. DOI: https://doi.org/10.1002/arp.1822.

Orengo, HA, Conesa, FC, Garcia-Molsosa, A, Lobo, A, Green, AS, Madella, M and Petrie, CA. 2020 Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data. Proceedings of the National Academy of Sciences – PNAS 117(31): 18240–18250.

Santos, J, Nunes, DAP, Padnevych, R, Quaresma, JC, Lopes, M, Gil, J, Bernardes, JP and Casimiro, TM. 2024 Automatic ceramic identification using machine learning. Lusitanian amphorae and Faience. Two Portuguese case studies. Science and technology of archaeological research 10(1).

Tanti, M, Berruyer, C, Tafforeau, P, Muscat, A, Farrugia, R, Scerri, K, Valentino, G, Solé, VA and Briffa, JA. 2021 Automated segmentation of microtomography imaging of Egyptian mummies. PloS one 16(12): e0260707–e0260707.

Wilkinson, MD, Dumontier, M, Aalbersberg, IjJ, Appleton, G, Axton, M, Baak, A, Blomberg, N, Boiten, et al. 2016 The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3(1): 160018. DOI: https://doi.org/10.1038/sdata.2016.18.

Zhao, X, Shu, C, Jiang, S and Hu, Y. 2023 From classification to matching: A CNN-based approach for retrieving painted pottery images. Digital Applications in Archaeology and Cultural Heritage 29: e00269-.

Zickel, M, Gröbner, M, Röpke, A and Kehl, M. 2024 MiGIS: micromorphological soil and sediment thin section analysis using an open-source GIS and machine learning approach. Eiszeitalter und Gegenwart 73(1): 69–93.

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S10: Is It All Fun and Games?: The Value(s) of Archaeogaming and other Forms of Play in Digital Heritage and Archaeology

Session Organisers:
Aris Politopoulos, Leiden University
Angus Mol, Leiden University
Sebastian Hageneuer, University of Cologne
Despoina Sampatakou, University of Glasgow

Description

Session Format: Standard

What is the value of games and play for (digital) archaeology? This is the question that lies at the roots of archaeogaming and it is the one that powers this session. As archaeogaming is established and growing, answers to it have come and will come from many places. These include archaeological studies focusing on video games specifically, but insights have and will also be drawn from other playful tools and media, such as board games, for research, education, outreach, or entertainment. What are the values driving these media and tools and how do they afford and constrain archaeological practice and perspectives on heritage and archaeology? Alternatively, papers in this session could focus on how professional archaeological and heritage practices, or popular imaginings thereof, shape these media in turn. With these guides, we follow in the footsteps of ‘traditional archaeogaming’ (Reinhard 2018), but emphatically seek to bring further the broader playful and mediatized perspectives therein. This session provides an entry point for new interventions in archaeogaming, opening up to voices and ideas not previously explicitly connected to archaeogaming or for budding ideas with much more room to grow. Deep dives into specific games or game series are welcomed, but contributors are also invited to consider how gaming and playing resides in many other archaeological and heritage practices. Perspective can come, for example, from the evaluation of digital play and storytelling in museums or other heritage projects. Contributors could consider how game engines and other game-focused computational tools are shaping digital archaeology. Papers can provide experience-based insights on the role of digital pleasure and entertainment in formal archaeology and heritage education or reflect on social media and other surveillance capitalist platforms as algorithmic artefacts for play. What is the role, for better or worse, of enchanting and extractive AI in game and heritage industries? These and other input from the broader and still largely unexplored cross sections, past and present, of analog and digital fun are encouraged. Underlying any specific case studies and by looking at the values and contexts of play, games, and archaeogaming, this session seeks to provide a more nuanced, reflective, and integrative perspective to either the optimistic views of early archaeological video game scholarship as well its more recent, somewhat crestfallen critiques (Politopoulos and Mol 2023; Reinhard 2024). Archaeogaming is a movement born in and out of playful, digital scholarship and the playfulness of the field of archaeogaming resides in its collective activities, which were and remain often unorthodox, experimental, or not in line with what academia would normally look like (Politopoulos et al. 2023). Still, what does it mean — what do playful artefacts and media, and their makers and researchers take on board — when play and fun is the central focus and guiding value for scholarship and the knowledge systems and wider communities it interfaces with? For example, it may be clear that having fun together remains a core archaeogaming practice and goal to this day, an enduring collaborative and knowledge-driven enchantment that hinges on committing to attentively and carefully studying and integrating (digital) play archaeologically (Graham 2022). Yet, following up on recent work in game studies (Trammel 2023; Mol et al. 2023), it is also clear that, while play can form a great basis for collaboration and sharing, it can also capture, bind, and get us stuck. Archaeogaming and other playful approaches in (digital) archaeology should therefore carefully consider what and who is played and who or what is being played with, potentially drawing in things and people resistant to play or inadvertently propping up play as a vessel for entrenched interests and narratives. So, is it all fun and games? This session wants to be wary of the captivating and conservative forces of play, while also exploring and advancing the mind- and toolsets required to foster diversity and accessibility in play-based, digital knowledge and creative work. In short, we welcome all archaeologists and all other playmakers and players who are invested in critically and constructively discussing the values of our digital playgrounds.

References

Graham, S., 2022. An enchantment of digital archaeology: raising the dead with agent-based models, archaeogaming and artificial intelligence. Berghahn Books.

Mol, A.A.A., A. Politopoulos, and S. Lammes, 2023. On Being Stuck in Sid Meier’s Civilization: The Promise of Freedom in Historical Games. In Conference Proceedings of DiGRA 2023 Conference: Limits and Margins of Games Settings.

Politopoulos A. and A.A.A. Mol, 2023: Critical miss? Archaeogaming as fun yet slippery tools for archaeological research and outreach. In K. Lambers and T. Kalayci (eds), Digital Archaeology. Promises and Impasses (Analecta Praehistorica Leidensia 51) Sidestone, 113-127.

Politopoulos A, A.A.A. Mol and S. Lammes, 2023. Finding the fun. Towards a playful archaeology. Archaeological Dialogues 30(1),1-15.

Reinhard, A., 2018: Archaeogaming. An introduction to archaeology in and of video games. Berghahn Press.

Reinhard, A., 2024. Archaeogaming: The State of the Field in 2022. In L.-J. Richardson, A. Reinhard and N. Smith (eds.) The Routledge Handbook of Archaeology and the Media in the 21st Century, Routledge, 135-151. Trammel, A. 2023. Repairing Play. A Black Phenomenology. MIT Press.

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S11: Connecting the Physical and Digital: Exploring Human-Intermediated Object Data Gathering

Session Organisers:
Aleks Michalewicz, University of Melbourne
Karen Thompson, University of Melbourne

Description

Session Format: Standard

More and more, information from collections of archaeological objects is being analysed digitally which could include qualitatively, quantitatively, statistically, by models and machine learning. As self-evident, the accuracy of such data is vital to the value of resulting analytic work and interpretation. When we consider information that objects can provide, there are two ways such data can be gathered. First is digital acquisition, such as 3D scans or photogrammetry, where the data collection machine mediates between the object and the data holding/storage machine. Data fidelity is primarily a matter of technological quality and user expertise for digital data acquisition. Second, and the focus of this session, is physical acquisition: data collected from the object by a human. This can include measurements, colour, and other characteristic features. Human-intermediated data gathering – using our hands and our eyes – remains important to digital data work and is relied upon where digital acquisition is unsuitable or unavailable. But when data is gathered by a human, other data integrity considerations become critical. These include what features of the object are considered worth the time to collect (i.e., inclusion versus exclusion), the precision of any measurements or descriptions (e.g., millimeters versus centimeters, constrained vocabulary versus free-text fields, colourimetry versus free-text colour descriptions), controls in the transcription protocol (from analogue [pen on paper] to digital [spreadsheet or database]), if data is collected by a single person or coalesced from multiple independent assessors, and more. Additional challenges are faced when using legacy data, and when aggregating digitally acquired data with human-intermediated data. All of these have implications for digital archiving, data reuse and open scholarship, and the value of data as research (specifically archaeological) resource and as a digital asset. It is all too easy for a user of data held digitally to imagine the data as somehow separate from the physical (and human) world. However, humans are fallible, and data errors occur. It is our experience that accounting for these expected (yet potentially hidden) errors in the subsequent computational work is often missing or at best underexplained. It is important to acknowledge the expectation of errors and describe the resultant uncertainty around any research outcome. This is not a criticism of the humans involved in the data collection, but rather honours their work and recognises the frailty of the data collection system. We propose that explanations should be required as part of the methodology of anyone using such data so as to develop more nuanced and reflexive understandings of the past. We invite participants to submit papers sharing their experiences in collecting data from objects and working with such data, with the aim of promoting dialogue and sharing perspectives on challenges as well as effective strategies and protocols. We invite contributions on these and related topics, practice-based case studies and in response to the questions below:

  • How does gathering data from a collection of objects change our relationship with those objects, and with the data?
  • How does data evolve when it is possible to revisit the object to correct or confirm digital information?
  • To what extent does knowing how the data will be used determine how, and what, data is collected?
  • Is the resourcing cost of multiple data collectors, instead of one person, justified by improvements in data quality or does this potentially introduces complications?
  • Does data in a beautifully organised data structure have the (unearned) impression of being more accurate than data held less formally?
  • What qualitative and quantitative approaches are particularly useful for collecting data from objects and working computationally with that data?
  • What happens at the interface of the physical object, human-intermediated data and digitally born data? What happens when we are working with different knowledge systems?
  • How does human-intermediated data collection intersect with ‘small data’ or ‘slow’ methodologies and/or theories, and how might this inform digital and computational data work?

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S12: Generative AI and Text Mining – using big models for big problems

Session Organisers:
Alex Brandsen, Leiden University
Alfie Lien-Talks, York University, Historic England and Archaeology Data Service

Description

Session Format: Standard

This session explores the impact of generative AI and text mining in archaeology, focusing on how these technologies are revolutionising data analysis and interpretation. Experts will discuss innovative applications, case studies, and the ethical challenges of using AI to uncover new insights into our ancient past. The above paragraph was generated using ChatGPT 4o, with the prompt “Generate a short abstract for a session proposal on the use of generative AI and text mining in archaeology”. While it’s quite generic, and sounds very typically GPT-style, it does capture the main idea of this session. But in more detail: Artificial Intelligence (AI) and Machine Learning (ML) approaches are becoming increasingly popular within archaeological research, as also evident by the large numbers of papers on this topic at the last couple of CAA conferences. Since the release of ChatGPT 3 in 2022, we are seeing a huge hype for generative AI (genAI), both in science and archaeology, and in society in general. Some applications have already been explored within archaeology, and it seems that this is a promising area to investigate further. But is the hype justified, or are we just using huge amounts of GPU power, electricity, and resources for subpar and non-meaningful results? While the main focus of this session will be genAI, we also wanted to include all other papers relating to Text Mining and Information Retrieval. These topics, closely related to Large Language Models (LLMs) like ChatGPT, often fall outside the scope of other sessions but are critical to understanding the full impact of AI in archaeology. We specifically invite authors to submit papers on the ethical issues related to genAI, papers comparing closed source vs. open source models, and research where genAI underperforms compared to other methods. Besides this, we invite authors to submit papers relating to the following themes:

  • The use of genAI for text generation, writing, and/or coding,
  • Using genAI for data processing, analysis, and information extraction,
  • Prompt engineering,
  • How to deal with the non-determinism of LLMs,
  • The use of image genAI for scientific purposes,
  • GenAI for 3D modelling,
  • Generative Adversarial Networks and their applications within archaeology and heritage,
  • Research dealing with other LLMs or Transformer based architectures, such as BERT,
  • Other Text Mining and Information Retrieval applications (also non-genAI methods),
  • (Theoretical) investigations into the ethical and environmental issues surrounding these large models,
  • Any other research relating to similar topics

For practical approaches we would encourage a critical dialogue to identify individual and shared problems, opportunities, and solutions. We invite authors to provide a thorough explanation and evaluation on their approach. If a classification problem is tackled, please use the standard evaluation metric for that task (e.g. F1 / precision / recall). By addressing both the opportunities and the limitations of Generative AI and Text Mining in archaeology, this session aims to contribute to the development of robust, standardised, and ethically sound practices within the field.

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S13: Computational innovations in biological anthropology, archaeology and genetics: advancing research on past human populations

Session Organisers:
Elissavet Ganiatsou, Democritus University of Thrace
Maxime Brami, Johannes Gutenberg University Mainz
Panagiota Bantavanou, Democritus University of Thrace

Description

Session Format: Standard

Biological anthropology and related fields, such as archaeology, molecular and population genetics, provide insights into past human populations, including genetic ancestry (Clemente et al., 2021; Marchi et al., 2022), dietary adaptations (Beaumont & Montgomery, 2016; Keenleyside et al., 2006; Varano et al., 2020), mobility (Knipper et al., 2017; Toncala et al., 2020; Whelton et al., 2018), and changes in skeletal morphology (Aidonis et al., 2023; Karakostis et al., 2017). In recent years, the field has undergone a transformative evolution with the introduction of advanced computational approaches (Cocozza et al., 2021; Klein et al., 2023; Fernandes et al., 2015; Ganiatsou et al., 2023; Li et al., 2022; Ringbauer et al., 2024; Stock et al., 2018; Tsutaya & Yoneda, 2013). These approaches enable the study of high-dimensional data and pave the way for innovative interdisciplinary big data research. This session aims to explore the impact of computational approaches, including artificial intelligence (AI), on biological anthropology and related fields. We welcome contributions that integrate machine learning, data mining, and/or deep learning through presentation of original research, methodological innovations and case studies. Topics of interest include, but are not limited to:

  • Dietary reconstruction and mobility using isotopic analysis.
  • Geometric morphometrics for analysing skeletal and grave morphology.
  • Facial reconstructions based on automatic skull-to-face transformation.
  • Demographic insights into past populations from skeletal data.
  • Advances in population genetics and ancient DNA research.

The session seeks to establish a collaborative network of researchers interested in advanced computational approaches in biological anthropology and related fields. Specific objectives of the session include:

  • Understanding how AI and big data are reshaping biological anthropology.
  • Providing a forum for experts in isotopic analysis, geometric morphometrics, ancient DNA, histology, and molecular techniques to share insights and methodologies.
  • Exploring cutting-edge computational approaches and their applications in anthropology.
  • Promoting interdisciplinary dialogue among archaeologists, biologists, computer scientists, and related fields to foster collaborative research.

This session is tailored for researchers, practitioners, and graduate students interested in leveraging computational approaches to advance their research in biological anthropology. Participants will gain insights into the latest workflows, software, and collaborative opportunities shaping the future of anthropological research.

References

Aidonis, A., Ganiatsou, E., Georgiadou, A., Souleles, A., Korelidou, M., Bantavanou, P., Kalliga, E., & Papageorgopoulou, C. (2023). The Part and Parcels of a City. The Impacts of Urbanization on the Population of Ancient Thessaloniki. Computer Applications and Quantitative Methods in Archaeology (CAA), , Amsterdam, Netherlands.

Beaumont, J., & Montgomery, J. (2016). The Great Irish Famine: Identifying Starvation in the Tissues of Victims Using Stable Isotope Analysis of Bone and Incremental Dentine Collagen. PloS One, 11(8), e0160065.

Clemente, F., Unterländer, M., Dolgova, O., Amorim, C. E. G., Coroado-Santos, F., Neuenschwander, S., Ganiatsou, E., Cruz Dávalos, D. I., Anchieri, L., Michaud, F., Winkelbach, L., Blöcher, J., Arizmendi Cárdenas, Y. O., Sousa da Mota, B., Kalliga, E., Souleles, A., Kontopoulos, I., Karamitrou-Mentessidi, G., Philaniotou, O., … Papageorgopoulou, C. (2021). The genomic history of the Aegean palatial civilizations. Cell, 184(10), 2565-2586.e21.

Cocozza, C., Fernandes, R., Ughi, A., Groß, M., & Alexander, M. M. (2021). Investigating infant feeding strategies at Roman Bainesse through Bayesian modelling of incremental dentine isotopic data. International Journal of Osteoarchaeology, 31(3), 429–439.

Fernandes, R., Grootes, P., Nadeau, M.-J., & Nehlich, O. (2015). Quantitative diet reconstruction of a Neolithic population using a Bayesian mixing model (FRUITS): The case study of Ostorf (Germany). American Journal of Physical Anthropology, 158(2), 325–340.

Ganiatsou, E., Souleles, A., & Papageorgopoulou, C. (2023). WEaning Age FiNder (WEAN): a tool for estimating weaning age from stable isotope ratios of dentinal collagen. Archaeological and Anthropological Sciences, 15(4), 50.

Karakostis, F. A., Hotz, G., Scherf, H., Wahl, J., & Harvati, K. (2017). Occupational manual activity is reflected on the patterns among hand entheses. American Journal of Physical Anthropology, 164(1), 30–40.

Keenleyside, A., Schwarcz, H., & Panayotova, K. (2006). Stable isotopic evidence of diet in a Greek colonial population from the Black Sea. Journal of Archaeological Science, 33(9), 1205–1215.

Klein, K., Wohde, A., Gorelik, A. V., Heyd, V., Diekmann, Y., & Brami, M. (2023). AutArch: An AI-assisted workflow for object detection and automated recording in archaeological catalogues. ArXiv, abs/2311.17978. https://doi.org/10.48550/arXiv.2311.17978

Knipper, C., Mittnik, A., Massy, K., Kociumaka, C., Kucukkalipci, I., Maus, M., Wittenborn, F., Metz, S. E., Staskiewicz, A., Krause, J., & Stockhammer, P. W. (2017). Female exogamy and gene pool diversification at the transition from the Final Neolithic to the Early Bronze Age in central Europe. Proceedings of the National Academy of Sciences, 114(38), 10083–10088.

Li, Y., Wang, J., Liang, W., Xue, H., He, Z., Lv, J., & Zhang, L. (2022). CR-GAN: Automatic craniofacial reconstruction for personal identification. Pattern Recognition, 124, 108400.

Marchi, N., Winkelbach, L., Schulz, I., & Brami, M. (2022). The genomic origins of the world’s first farmers. Cell. https://www.cell.com/cell/pdf/S0092-8674(22)00455-X.pdf

Ringbauer, H., Huang, Y., Akbari, A., Mallick, S., Olalde, I., Patterson, N., & Reich, D. (2024). Accurate detection of identity-by-descent segments in human ancient DNA. Nature Genetics, 56(1), 143–151.

Stock, B. C., Jackson, A. L., Ward, E. J., Parnell, A. C., Phillips, D. L., & Semmens, B. X. (2018). Analyzing mixing systems using a new generation of Bayesian tracer mixing models. PeerJ, 6, e5096.

Toncala, A., Trautmann, B., Velte, M., Kropf, E., McGlynn, G., Peters, J., & Harbeck, M. (2020). On the premises of mixing models to define local bioavailable 87Sr/86Sr ranges in archaeological contexts. The Science of the Total Environment, 745, 140902.

Tsutaya, T., & Yoneda, M. (2013). Quantitative Reconstruction of Weaning Ages in Archaeological Human Populations Using Bone Collagen Nitrogen Isotope Ratios and Approximate Bayesian Computation. PloS One, 8(8), e72327.

Varano, S., De Angelis, F., Battistini, A., Brancazi, L., Pantano, W., Ricci, P., Romboni, M., Catalano, P., Gazzaniga, V., Lubritto, C., Santangeli Valenzani, R., Martínez-Labarga, C., & Rickards, O. (2020). The edge of the Empire: diet characterization of medieval Rome through stable isotope analysis. Archaeological and Anthropological Sciences, 12(8), 196.

Whelton, H. L., Lewis, J., Halstead, P., Isaakidou, V., Triantaphyllou, S., Tzevelekidi, V., Kotsakis, K., & Evershed, R. P. (2018). Strontium isotope evidence for human mobility in the Neolithic of northern Greece. Journal of Archaeological Science: Reports, 20, 768–774.

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S14: Advances in modelling past human ecosystems

Session Organisers:
Eleftheria Paliou, University of Cologne
Andreas Angourakis, Ruhr University Bochum; University of Cologne
Maria Elena Castiello, University of Lausanne; Marek Vlach Institute of Archaeology of the Czech Academy of Science

Description

Session Format: Standard

In recent years, there has been a steady increase in the number of anthropological and archaeological studies that look into the human-environment interactions and resource management practices of Indigenous and local populations (Sherjon et. al. 2015; Whitaker et al. 2023; Pisor and Jones 2021; Welch-Devine et al. 2020). Such works, which often draw from the fields of historical ecology, pyrogeography, multi-species studies and climate ethnography, have provided a wealth of new data on human experiences, perceptions and adaptations to ecological change and novel insights into human-animal and human-plant interactions at a variety of spatial and temporal scales. At the same time, there has been an increase in interdisciplinary eco-archaeological approaches that make best use of archaeological science methods to provide evidence of long- and short-term change in human ecosystems. These developments offer new opportunities for enriched approaches to computational modelling that better address important scientific challenges in the study of past human eco-dynamics (Kintigh et. al. 2014).

This session invites papers on archaeological computational models that seek to take more fully into account advancements shaping the current discourse in socio-ecological research. We are particularly interested in approaches to simulation modelling that gain insights from Indigenous and traditional ecological knowledge. We also encourage contributions that explore the socio-ecological dynamics of resource use, depletion and renewal and in interdisciplinary eco-archaeological approaches that bring together ethnoarchaeology, archaeological science methods, and computational modelling. More broadly, we invite works on computational modelling (e.g., simulations, GIS-based models, equation-based models, agent-based models, etc.) which look into:

  • the response of hunter-gatherer, agropastoralist and urban populations to ecological change
  • anthropogenic impacts on the environment in the long- and short-term, at smaller and larger spatial scales
  • ecological sustainability and resilience in the past and present
  • theoretical and conceptual frameworks for socio-ecological simulations of past human behaviour that go beyond traditional models (e.g., optimal foraging theory)
  • technological advances in computational modelling of socio-ecological systems.

The theme of this session aims to complement a workshop that took place in Cologne in May 2024 https://ecosystem-modelling.uni-koeln.de/programme ), and is linked to a JCAA Special Collection on the same topic that invites relevant contributions throughout 2025 (https://journal.caa-international.org/special-collections ). Although there is a separate paper selection and submission process for the Special Collection, the CAA 2025 session aims to offer prospective authors the opportunity to meet and discuss diverse approaches to advancing computational models of past human ecosystems. Paper abstracts from authors who are not interested in submitting their work for publication in the JCAA Special Collection are also very welcome.

References

Kintigh, Keith W., Jeffrey H. Altschul, Mary C. Beaudry, Robert D. Drennan, Ann P. Kinzig, Timothy A. Kohler, W. Fredrick Limp, et al. 2014. ‘Grand Challenges for Archaeology’. American Antiquity 79 (01): 5–24. https://doi.org/10.7183/0002-7316.79.1.5.

Pisor, Anne C., and James H. Jones. 2021. ‘Human Adaptation to Climate Change: An Introduction to the Special Issue’. American Journal of Human Biology 33 (4): e23530. https://doi.org/10.1002/ajhb.23530.

Scherjon, Fulco, Corrie Bakels, Katharine MacDonald, and Wil Roebroeks. 2015. ‘Burning the Land: An Ethnographic Study of Off-Site Fire Use by Current and Historically Documented Foragers and Implications for the Interpretation of Past Fire Practices in the Landscape’. Current Anthropology 56 (3): 299–326. https://doi.org/10.1086/681561.

Welch-Devine, Meredith, Anne Sourdril, and Brian J. Burke, eds. 2020. Changing Climate, Changing Worlds: Local Knowledge and the Challenges of Social and Ecological Change. Ethnobiology. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-37312-2.

Whitaker, James Andrew, Guillaume Armstrong, and Chelsey Geralda Odonne, eds. 2023.Climatic and Ecological Change in the Americas: A Perspective from Historical Ecology. London: Routledge. https://doi.org/10.4324/9781003316497

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S15: Digital bioarcheology: new approaches for old problems

Session Organisers:
Manon Vuillien, Côte d’Azur university
Vanna Lisa Coli, Côte d’Azur university
Pauline Garberi, Côte d’Azur university

Description

Session Format: Standard

Studying the diversity of living and fossilised organisms in biology and palaeontology is inextricably linked to the work of mathematicians. Since the ground-breaking work of the zoologist and mathematician D’Arcy Thompson at the beginning of the 20th century, there have been significant advances in the methodology used to study the variability of biological forms due to the integration of geometric perspectives (Bookstein, 1978; 1996). The rise of computational methods in shape analysis combined with the widespread use of 3D imaging in the 1990s has enabled new and innovative advancements in the analysis and virtual recognition of biological forms.

The use of computational techniques in the analysis of biological archives (faunal and botanical remains) from archaeological contexts is a relatively recent phenomenon. This could be attributed to several factors. Firstly, the intrinsic characteristics of bioarchaeological remains give rise to various complications and present specific difficulties. The deployment of computational quantitative approaches is highly dependent on the availability of large amounts of comparable digital data in 2D or 3D. However, these data are frequently inaccessible. Secondly, the preservation of faunal and botanical remains is rarely optimal due to their original function (e.g. food waste) and the conditions under which they were buried, found and stored. Thirdly, the inter– and intra-individual variability of past plants and animals is based on partial data that are often challenging to compare with current data. In light of these challenges, it is crucial to integrate the expertise of bioarcheologists with machine learning and statistical methods. In that sense, the application of supervised and unsupervised machine learning techniques, as demonstrated by studies such as those of Miele et al. (2020) and Bonhomme et al. (2023), was helpful to address current biosocial questions such as the domestication process and biogeographic history of mammals, as well as the dynamics of human settlements and their role in the emergence of commensal animals and the evolution of terrestrial ecosystems. A larger involvement of applied mathematics experts into interdisciplinary works on bioarchaeology questions will assure steady advancements to both disciplines.

The goal of this session is to bring together, for the first time, interdisciplinary research led by bioarchaeologists and mathematicians. This session will explore how the use of machine learning techniques has been integrated into studies of faunal and plant remains to improve our understanding of human-nature interaction over long periods of time. Expected contributions to this session will include works on:

  • Supervised or unsupervised learning strategies for the taxonomic identification of faunal and plant remains from interspecific to intraspecific scales;
  • Use of machine learning techniques to model animal and human mobility and, by extension, past landscapes and environments;
  • Methodological developments in applied mathematics in relation to the nature and conservation of bioarchaeological remains;
  • How to address the issue of archaeological dataset management (dataset size, preservation, nature…)
  • Comparisons between supervised and unsupervised learning methods and analytical methods used in bioarchaeology, such as biometrics or geometric morphometric methods;
  • How to incorporate expert knowledge into models.

Contributions on ongoing research projects that focus on feasibility and/or obstacles encountered are also welcome. Expected contributions are not limited to a particular period or world region. Contributions from young researchers to present their research findings are encouraged. To facilitate productive exchanges, several moments will be dedicated to discussions during the session, with the aim to encourage questions and collaborations.

References

Bookstein, F.L., 1996. Biometrics, biomathematics and the morphometric synthesis. Bulletin of Mathematical Biology 58, 313–365. http://dx.doi.org/10.1016/0092-8240(95)00329-0

Bookstein, F.L., 1978. The Measurement of Biological Shape and Shape Change, Springer. ed, Lecture Notes in Biomathematics. Springer Science & Business Media, New-York.

Bonhomme, V., Bouby, L., Claude, J., Dham, C., Gros-Balthazard, M., Ivorra, S., Jeanty, A., Pagnoux, C., Pastor, T., Terral, J.-F., Evin, A., 2023. Deep learning versus geometric morphometrics for archaeobotanical domestication study and subspecific identification (preprint). Bioinformatics. https://doi.org/10.1101/2023.09.15.557939

Miele, V., Dussert, G., Cucchi, T., Renaud, S. (2020). Deep Learning for Species Identification of Modern and Fossil Rodent Molars. bioRxiv, 2020.08.20.259176. https://doi.org/10.1101/2020.08.20.259176.

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S16: Reuse, remix, recycle: putting the R in FAIR archaeological data

Session Organisers:
Aida Fadioui, University of Antwerp
Jane Jansen, Arkeologerna
Stephen Stead, Paveprime Ltd
Chiara Giovannetti, Sapienza University of Rome

Description

Session Format: Standard

The archaeological research community was an early adopter of digital tools for data acquisition, organisation, analysis, and presentation of research results (Richards 2022). As several projects have shown, digital data can be shared, but how can that data be used? To address those questions, principles and ontologies have been created and are ready to be applied, allowing an easy understanding of the semantics of each dataset. Modeling archaeological data for the semantic web offers indeed a range of advantages largely related to findability, interoperability and reusability (according to the FAIR principles). Digital archive access projects will revolutionise archaeological research and are vital if we want to attain the R in FAIR.

CRMarchaeo, an extension of the CIDOC CRM, is one way to link a wide range of existing documentation from archaeological investigations. It was created to promote a shared formalisation of the knowledge extracted from archaeological observations. It provides a set of concepts and properties that allow clear explanation (and separation) of the observations and interpretations made, both in the field and in post-excavation. Using FAIR principles is critical to the creation of wider pictures of regions or periods and can also be a stepping stone to generating Big Data for further analysis. But a healthy discussion on the application of the FAIR principles is required to ensure that best practice emerges by consensus rather than coup d’état.

At the same time, public archaeology, community archaeology and participatory design approaches are all ideas that have spread and are changing the way we do research. Can we model our data to fulfill the associated promises? The question is valid since building data models from the bottom up, based on people’s experiences, their needs and expertise, usually still means that there are still final decisions to be made, since data modeling is essentially a process of structuring at the expense of multiple meanings and alterity. Crafting models that allow us to explore multiple relationships and which support polyvocality is one of the new challenges we are facing.

The data born from the archaeological process is incredibly diverse, but not all of it is recorded, and when it is, not necessarily findable and reusable. We need a body of proficient professional and amateur practitioners able, and willing, to discuss their approaches and experience. This may include the application of CRMarchaeo to describe and encapsulate the semantic meaning of archaeological archives of all eras but it may also encapsulate other ontologies and approaches.In this session, we’re aiming to discuss the colorful scenario of modeling archaeological data for the semantic web.

We will address the integration of the wide range of archaeological excavation archive materials using suitable ontologies. It is also intended to address electronic excavation databases of all flavours and vintages being made interoperable without the need to harmonise away the unique qualities and flavours of chosen excavation methodologies. The materials tackled could include historic daybook or narrative text descriptions of archaeological excavations or chance encounters as well as more modern context sheet paper records of systematic excavations. We are very interested in the generation of Linked-Open-Data (LOD) from these archive resources and particularly welcome contributions in this area; we are particularly interested in applications of the CIDOC CRM and its extension CRMarchaeo but all approaches will be welcomed.

On the other side, we are seeking projects that try to capture data that escape the standard categorizations in use. Projects that are crafting models that allow us to explore multiple relationships, which try to support polyvocality, and which experiment with new ways to engage with the archaeological record. “Nonstandard” data could be related to, among others, multisensory experience (e.g. smell, sound); storytelling; and representing the uncertain, absurd, emotional and embodied. What stones are left unturned, or are turned that we are not aware of since they happen to be in the context of “other” places and communities? What data do we know that could further enrich what we have?

As such, we aim to create a space for discussion, addressing current challenges, but also sharing best practices, established methodologies, and both positive and negative work experiences. These could include archaeologists depositing new excavation archives; researchers working with existing archives; projects in the phase of data collecting; researchers/projects crafting models to optimize reuse. Curators and archivists could also inform the debate. In this session we welcome project outputs that successfully integrated data from heterogeneous sources, fruitful examples of reuse, practical insights into work methodologies, and (why not?) stories of unsuccessful experiments that show where we can improve.

References

de Castro, E. V. (2015). Who is Afraid of the Ontological Wolf?: Some Comments on an Ongoing Anthropological Debate. The Cambridge Journal of Anthropology, 33(1), 2–17.

Hacıgüzeller, P., Taylor, J. S., & Perry, S. (2021). On the Emerging Supremacy of Structured Digital Data in Archaeology: A Preliminary Assessment of Information, Knowledge and Wisdom Left Behind. Open Archaeology, 7(1), 1709–1730. https://doi.org/10.

Huggett, J. (2018). Reuse Remix Recycle: Repurposing Archaeological Digital Data. Advances in Archaeological Practice, 6(2), 93–104. https://doi.org/10.

Richards, J. 2022, Presentation at CHNT Vienna https://cidoc-crm.org/collaborations

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S17: Comparing the Incomparable: Managing and Analyzing Data from Heterogeneous Sources in Archaeological Research

Session Organisers:
Fabian Riebschläger, German Archaeological Institute, NFDI4Objects
Lisa Steinmann, German Archaeological Institute, NFDI4Objects
Julian Hollaender, Landesamt für Denkmalpflege / State Office for Heritage Baden-Württemberg, NFDI4Objects

Description

Session Format: Standard

Archaeological data collection is inherently diverse. Different archaeologists often document the same entities in very different ways. Data models are shaped by factors like excavation type (e.g., research excavation, rescue excavation, survey, building survey, material study), documentation scale (mass recording vs. detailed studies), methods used, research questions, geographical and temporal scope, and even the tools and software employed. On top of that, documentation standards and conventions for data recording vary widely across projects, and there is no agreed-upon minimal standard within the multitude of archaeologies, worldwide – let alone the discipline as a whole –, to enable comparability on a more basic level. Although many individual archaeologists and numerous national and international initiatives, such as NFDI4Objects, are now addressing this problem, there is still no satisfactory solution. This session therefore showcases concrete examples that have overcome these challenges, focusing on exploring the methods for integrating and comparing heterogeneous data from multiple varying sources, each with unique objectives and documented in different scales and depths.

Key questions the session will address include:

  • How can data from various sources (e.g., finds from different sites, objects in different online collections, all of which are collected or published by different researchers and institutions) be effectively used to create genuine new research questions, especially outside the initial boundaries of the data sets?
  • What are useful tools and methods that allow heterogeneous data from varied sources to be effectively harmonized, integrated and compared, despite being collected at diverse scales, from mass surveys to focused case studies, and by different projects and people?
  • How can different data models representing the same real-world entities be mapped onto each other without resulting in loss or distortion of information?
  • How can data that has been recorded and stored in different applications or online databases be made interoperable?
  • Which insights can be gained from such case studies, that would help data infrastructures to better store, manage, and connect such diverse data?

In archaeological practice, especially. in the fieldwork, there is currently no universal documentation tool that meets the varied requirements for integrating data of the aforementioned complexity, and the development of one is unlikely in the near future, or perhaps even undesirable given our diverse research. On top of that, it is even more unlikely that archaeologists across all disciplines will decide to use a unified tool or data model for their research. Therefore, this session will explore alternative roads leading to the ultimate goal of the FAIR principles (Findability, Accessibility, Interoperability, and Reusability). If the data we want to work with is not interoperable – how can we make it so?

This session will explore the practical solutions from specific projects that have attempted to integrate, analyze and publish data from different sources, and the strategies and tools they have applied to achieve this. If parts of the data can be coerced into the same format, it suggests that each of the sources had the intention to record the same concepts. The insights gained from this can help to develop infrastructures that can better address these challenges in the future: the different case studies could highlight the common ground of minimal standards that are actually used by researchers.

The results from this session will also strengthen the ongoing efforts within NFDI4Objects, particularly the development of common “minimum information standards” aimed at ensuring data from diverse projects remains comparable and accessible. This initiative seeks to harmonize documentation standards while allowing flexibility for the specific conditions of each project, with a long-term goal of making harmonized data available.

We invite submissions on the following topics:

  • Case studies showcasing successful integration of data gathered from different sources. This could be quantitative or qualitative archaeological or archaeometric data.
  • Innovative approaches, methods and tools for integrating or aggregating differently formatted data from any field pertaining to archaeology ensuring the possibility for a comprehensive analysis while maintaining data integrity.
  • The role of AI and machine learning in automating data aggregation and integration and the possibilities AI provides for merging and discovering similarities across originally non interoperable data models.
  • Projects that retrofit old databases and archives to comply with existing standards.
  • Solutions to common data comparability challenges, such as standardizing metadata, developing minimum information standards, and applying ontological frameworks.

This session aims to foster collaborative dialogue on how to compare the incomparable in archaeological research, addressing the challenges of managing heterogeneous data. By incorporating insights from NFDI4Objects and showcasing practical solutions for handling diverse datasets, this session will provide participants with valuable frameworks to improve data comparability and interoperability in their own research.

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S18: Teaching with Tech: Bringing Archaeological Pedagogy into the Future

Session Organisers:
Robert Stephan, University of Arizona
Montine Rummel, Sapienza Università di Roma
Caleb Simmons, University of Arizona
Aviva Doery, University of Arizona

Description

Session Format: Standard

In the evolving landscape of higher education, digital technologies are transforming how archaeology is taught at the university level, enhancing both pedagogical methods and student engagement. This session will explore how innovative digital tools—such as virtual reality (VR), augmented reality (AR), video games, and other emerging technologies—are improving archaeological education by creating immersive, interactive, and experiential learning environments that bring the past to life for students. Archaeological education has traditionally relied on lectures, textbooks, and fieldwork to convey the richness of past cultures. However, the integration of digital tools now allows students to virtually interact with ancient sites and artifacts, simulating fieldwork experiences (Garstki et al. 2019), fostering critical thinking (Angelleli et al. 2023), and broadening access to these once physically restricted experiences (Corrales-Serrano et al. 2024). Recent studies have shown that digital platforms enhance student understanding and retention of archaeological concepts by engaging them in ways that traditional teaching methods cannot (see Lund & Wang 2019 for VR/AR; see Squire 2011 and Young et al. 2017 for video games). This session will examine the multifaceted role that these technologies play in archaeology education, from providing virtual dig experiences to enabling students to digitally reconstruct ancient artifacts and environments. By incorporating case studies from leading educators, the session will highlight how digital methods are being employed to make archaeology more accessible and engaging, particularly in university classrooms. Specific attention will be paid to how these tools help overcome the barriers that prevent students from participating in traditional fieldwork, such as financial limitations, work obligations, and geographical constraints. Technologies like VR offer students the opportunity to virtually travel to archaeological sites, engage with artifacts in 3D environments, and participate in simulations of excavation processes. Similarly, AR can enhance in-class experiences by overlaying digital content on physical models, providing students with interactive, real-time learning opportunities. Topics covered in this session may include:

  • Integrating VR and AR into archaeology curricula to create immersive virtual fieldwork and excavation experiences, allowing students to explore sites and artifacts in 3D environments.
  • Using video games and simulation platforms to engage students in interactive, gamified learning experiences, where they can role-play as archaeologists, manage dig sites, or reconstruct ancient civilizations.
  • Digital reconstructions of historical sites and artifacts for classroom use, enabling students to virtually handle and study objects that would otherwise be inaccessible.
  • Exploring digital storytelling methods, such as interactive media or web-based platforms, to immerse students in archaeological narratives, fostering deeper engagement and retention.
  • Leveraging 3D modeling and photogrammetry techniques to teach students how to digitally recreate artifacts and sites, offering hands-on experience with cutting-edge archaeological methods.
  • Addressing the ethical considerations of using digital technologies in archaeological education, ensuring cultural sensitivity, inclusivity, and academic integrity.

As university demographics and learning environments continue to evolve, so too must the tools we use to teach. This session invites educators, technologists, and archaeologists to share their experiences, successes, and challenges in integrating digital tools into archaeological education. Attendees will leave with new ideas and strategies for employing cutting-edge technologies in their own teaching, ultimately enhancing the educational experience for students and preparing them for a future where digital fluency in archaeology is crucial.

References

Angelleli, C. V., de Campos Ribiero, G. M., Severino, M. R., Johnstone, E., Borzenkova, G., & da Silva, D. C. O. (2023). Developing critical thinking skills through gamification. Thinking Skills and Creativity, 49, 101354.1-13. https://doi.org/10.1016%2Fj.tsc.2023.101354

Corrales-Serrano, M., Merchán, P., Merchán, M.J., and Pérez, E., 2024. Virtual reality applied to heritage in higher education – Validation of a questionnaire to evaluate usability, learning, and emotions. Heritage, 7(6), pp.2792-810. https://doi.org/10.3390/heritage7060132

 Garstki, K., Larkee, C., and LaDisa, J., 2019. A role for immersive visualization experiences in teaching archaeology. Studies in Digital Heritage, 3(1), pp.46-59. https://doi.org/10.14434/sdh.v3i1.25145

Lund, B. and Wang, T., 2019. Effect of virtual reality on learning motivation and academic performance: What value may VR have for library instruction? Kansas Library Association College and University Libraries Section Proceedings, 9(1), pp.1-7. https://doi.org/10.4148/2160-942X.1073

Squire, Kurt., and Henry Jenkins. Video Games and Learning : Teaching and Participatory Culture in the Digital Age. New York: Teachers College, 2011.

Young, Slota, Young, Michael F. D., and Slota, Stephen T. Exploding the Castle : Rethinking How Video Games and Game Mechanics Can Shape the Future of Education. 2017. Psychological Perspectives on Contemporary Educational Issues.

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S19: Reusable Digital Research Workflows for Archaeology

Session Organisers:
Agiatis Benardou, DARIAH
Émilie Pagé-Perron, ARIADNE
Anne Baillot, DARIAH
Julian Richards, ARIADNE

Description

Session Format: Standard

The field of Archaeology has greatly benefited from the advent of digital technologies, which have enhanced Humanities and Heritage research as a whole. These advancements have facilitated the application of complex methodologies to large datasets. Recent progress in Machine Learning methods has not only improved the quantity but also the quality of both input and output data. One of the significant advantages of computation-based methods is the efficiency gained in terms of time, energy, and knowledge. However, relying on this resource economy has introduced new challenges. Over the past decade, digital tools have become innovative selling points for funders, leading to the development of a plethora of tools that are often quite similar, rarely compatible, and frequently commercialised. This creates confusion for researchers seeking methodologies that can be reused and customised to their specific needs. Consequently, implementing Open Science principles has become increasingly challenging, both technically and in terms of communication within the research community. These issues are especially critical in Archaeology, given the diverse range of data and methods required throughout the research process. The ATRIUM project aims to provide concrete solutions for both data management and workflow reusability challenges in Archaeology. Advancing FronTier Research In the Arts and hUManities (ATRIUM, https://atrium-research.eu/) is a four-year European project aiming to facilitate access to, and bridge between, digital research infrastructures and advancing frontier knowledge with a focus on arts and humanities. Its 30 constituent partners endeavour, among other objectives, to prepare research workflows and associated demonstrators for the major usual computational research tasks on text, image, 3D, sound, and geographic data in the domain of Archaeology. Research infrastructures are key in the process of stabilising access to digital-based methods. They are in a position to provide virtual space for hosting, archiving, cataloguing information. But their strength lies not only in the material support they provide: it also has to do with their community of users who make up the backbone of a transdisciplinary dialogue – the key for scientific advances. It is one major role of research infrastructures to facilitate this dialogue by providing long-term support, identifying and contributing to relevant standardisation efforts, and enabling discoverability of research output. This session understands itself as a contribution to these dynamics. It is co-organised by DARIAH and ARIADNE, two research infrastructures dedicated to improve access to digital research tools, among others. The Digital Research Infrastructure for the Arts and Humanities (DARIAH, https://www.dariah.eu/) aims to enhance and support digitally-enabled research and teaching across the arts and humanities. It develops, maintains and operates an infrastructure in support of ICT-based research practices and sustains researchers in using them to build, analyse and interpret digital resources. ARIADNE (https://www.ariadne-research-infrastructure.eu/) is a research infrastructure for archaeology with the primary aim to enable access and promote discovery of resources and services. Its portal acts as a central point for discovering archaeological research datasets and other resources. The goal of this session is twofold: on the one hand, it aims at presenting reusable workflows such as they are being developed in the ATRIUM project (on 3D data, geographical data, OCR of grey literature, their annotation, reusability scenarios,…). On the other hand, we aim to invite researchers outside of the ATRIUM project working on similar questions and discuss together how they approach them. In particular, we are interested in the modelisation of research scenarios in a format more accessible than technical documentation that could be included as contributions to the SSH Open Marketplace (https://sshopencloud.eu/ssh-open-marketplace). With this call, we invite colleagues to submit papers which present the research workflows they are planning, have created, or adopted, discuss the state of reusability of workflows in a specific topical area, or other relevant papers under the thematic of our call. We encourage individuals of varied professional identity and from outside Europe to submit. We also encourage submissions related to challenges in accessing existing infrastructure, and solutions developed to overcome these challenges, or suggested steps infrastructures should take to improve the discoverability and access to their services in the context of archaeological research workflows.

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S20: “Scaling Heights”: Unveiling Mountainous Landscapes Through Interdisciplinary Survey Strategies, Quantitative Modelling and Computational Methods

Session Organisers:
Andriana-Maria Xenaki, University of Cambridge
Giannis Apostolou, Landscape Archaeology Research Group (GIAP)/ Catalan Institute of Classical Archaeology (ICAC)

Description

Session Format: Standard

INTRODUCTION

Despite their natural allure, mountainous landscapes are significantly underrepresented in archaeological literature (for some notable exceptions see papers in Pelisiak et al. 2018; Garcia-Molsosa 2022). The focus has predominantly been placed on the study of elite material culture expressed by the more ‘developed’ and complex centres of lowland and coastal regions. Modern researchers are also influenced by historical preconceptions, dating back to the Classical and Roman periods. Mountains were, and still are, perceived as wild, untamed spaces, emphasising the need (or the weakness) to domesticate and bring them under forms of state control (König 2016, 48). Such conceptual baggage has shaped social stereotypes of montane communities up to the 19th and 20th centuries (Robb et. al 2019, 6), restricting the study of upland sites as a one-sided dependent relationship with lowland power structures. It appears almost as if the uplands and the lowlands are divided into two worlds, brought together mostly in discussions about political geography and the exertion of control (e.g. fortification systems, peak sanctuaries, and the acquisition and appropriation of mountain resources). Consequently, mountainous landscapes remain marginally explored, with an emphasis on the study of specific types of sites and periods of habitation, namely those related to cultural peaks.

OBJECTIVE

We are welcoming papers that bring to the fore these often-overlooked landscape features through the examination of the long-term relationship between human activities (e.g. settlement evolution patterns, site location preferences, land use practices) and the environment (e.g. geography, climate change) with a particular emphasis on integrating results of regional archaeological surveys with recent multimethod and multiscale landscape archaeology approaches. In doing so, we aim to create a dialectic between the contribution of emerging methodologies and the weaving of archaeological narratives in montane landscapes.

INVITATION

Possible topics for presentations include, but are not limited to:

  • Survey Design and Research Questions: We consider contributions discussing the theoretical and methodological framework behind survey planning in mountainous areas. We also encourage exchanging feedback on practical limitations, empirical considerations and the shaping of research inquiries related to the study of montane cultural landscapes (Garcia-Molsosa 2022).
  • Legacy Survey Data: We invite presentations that focus on re-evaluating and integrating legacy survey data to facilitate a dynamic exchange between traditional and contemporary archaeological interpretations. We are particularly interested in contributions that treat legacy data as primary sources of information, rather than merely bibliographic references. Furthermore, presentations may address the challenges of aligning legacy data—often gathered with varying methodologies and standards—with modern datasets, including aspects of site cross-referencing and geolocation, site definition etc (Apostolou et al. 2024).
  • Modelling Settlement Patterns and Human-Landscape Interactions: We seek studies employing various spatial analysis methods, such as point pattern analyses and predictive modelling, to explore the dynamic settlement patterns and interactions between human populations and their surrounding environments (for general applications of point process models see Baddeley et al. 2016). While these methods are commonly applied in archaeological datasets (e.g. Bevan and Wilson 2013; Davis et al. 2020; Eve and Crema 2014; Spencer and Bevan 2019), their use in mountainous areas remains limited. In many cases the results from lowland studies are often inappropriately extrapolated to highland regions, resulting in a lack of specialised modelling that investigates mountains independently. We encourage critical applications of these methods while also considering their limitations pertaining to sample size, scale, and the quality of archaeological data incorporated in the models. Of particular interest could be the implementation of sensitivity analyses to assess the use of the terms “site” and “settlement” across different survey projects.
  • Remote Sensing and Machine Learning Applications: We also welcome approaches that use advanced mapping technologies and artificial intelligence applications, such as remote sensing datasets and machine learning algorithms, to detect, classify, and interpret archaeological sites in upland topographies (e.g. Berganzo-Besga et al. 2021; Fontana 2022). Of particular interest would be addressing challenges related to site visibility, taphonomic processes, and the potential for ground-truthing the results through field validation strategies.
CLOSING REMARKS

Through this session, we hope to bring together researchers who will push the research horizons in exploring montane landscapes by applying novel methodologies to overcome the inherent challenges of mountainous terrains. This way, we aspire to commence a dialogue between experts in mountain surveys, which will not only recognise but also manage to move beyond the conventional baggage and stereotypes historically associated with upland regions.

REFERENCES

Apostolou, G., Venieri, K., Mayoral, A., Dimaki, S., Garcia-Molsosa, A., Georgiadis, M. and Orengo, H. A., 2024. Integrating legacy survey data into GIS-based analysis: The rediscovery of the archaeological landscapes in Grevena (Western Macedonia, Greece). Archaeological Prospection 31 (1): 37-52. https://doi.org/10.1002/arp.1926

Baddeley, A., Rubak, E. and Turner, R., 2016. Spatial Point Patterns: Methodology and Applications with R. London and New York, CRC Press. https://doi.org/10.1201/b19708

Berganzo-Besga, I., Orengo, H. A., Lumbreras, F., Carerro-Pazos, M., Fonte, J. and Vilas-Estévez, B., 2021. Hybrid MSRM-based Deep Learning and multitemporal Sentinel 2-based Machine Learning algorithm detects near 10k archaeological tumuli in North-Western Iberia. Remote Sensing 13, 4181. https://doi.org/10.3390/rs13204181

Bevan, A. and Wilson, A., 2013. Models of settlement hierarchy based on partial evidence. Journal of Archaeological Science 40(5): 2415-2427. https://doi.org/10.1016/j.jas.2012.12.025

Davis, D. S., DiNapoli, R. J. and Douglass, K., 2020. Integrating point process models, evolutionary ecology and traditional knowledge improves landscape archaeology—A case from Southwest Madagascar. Geosciences 10(8), 1-25. https://doi.org/10.3390/geosciences10080287

Eve, S. J. and Crema, E. R., 2014. A house with a view? Multi-model inference, visibility fields, and point process analysis of a Bronze Age settlement on Leskernick Hill (Cornwall, UK). Journal of Archaeological Science 43, 267-277. https://doi.org/10.1016/j.jas.2013.12.019

Fontana, G., 2022. Italy’s Hidden Hillforts: A Large-Scale Lidar-Based Mapping of Samnium. Journal of Field Archaeology, 47(4): 245-261. https://doi.org/10.1080/00934690.2022.2031465

Garcia-Molsosa, Α. (Ed.), 2023. Archaeology of Mountain Landscapes: Interdisciplinary Research Strategies of Agro-Pastoralism in Upland Regions. Albany, State University of New York Press https://doi.org/10.1515/9781438489896

König, J., 2016. Strabo’s mountains, in McInerney, J., and Sluiter, I. (Eds.), Valuing Landscape in Classical Antiquity: Natural Environment and Cultural Imagination. Leiden and Boston: 46-49.

Pelisiak, A., Nowak, M. and Astaloş, C. (Eds.), 2018. People in the mountains: Current approaches to the archaeology of mountainous landscapes. Oxford, Archaeopress. https://doi.org/10.2307/j.ctv1pdrqpg

Robb, J., Chesson, M. S., Forbes, H., Foxhall, L., Forbes, H. F., Lazrus, P., Michelaki, K., Chiodo A. P. and Yoon, D., 2019. The 20th century invention of ancient mountains: the archaeology of highland Aspromonte. International Journal of Historical Archaeology 25(1): 14-44. https://doi.org/10.1007/s10761-020-00543-x

Spencer, C. and Bevan, A., 2019. Settlement location models, archaeological survey data and social change in Bronze Age Crete. Journal of Anthropological Archaeology 52: 71-86. https://doi.org/10.1016/j.jaa.2018.09.001

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S21: Moving Beyond Digital Fieldwork Documentation: Integrating and Preserving Archaeological Knowledge

Session Organisers:
James Taylor, University of York
Markos Katsianis, University of Patras,
Nicolò Dell’Unto, Lund University

Description

Session Format: Standard

Digital technologies have revolutionised archaeological fieldwork, transforming documentation through tools like 3D modelling, GIS mapping, and high-resolution imaging. Yet, while these innovations enhance data capture, the focus must now shift from documentation during fieldwork to the broader use of digital data in subsequent research stages. This session, ‘Moving Beyond Digital Documentation’, will explore how digital data is applied after fieldwork, its dissemination to various audiences, its long-term preservation, and its integration with traditional methods.

Maintaining consistent data quality within organisations and across long-term projects often requires well-structured workflows and dedicated resources, both in terms of technology and personnel. We seek to explore the challenges of maintaining effective workflows that examine how digital datasets—such as 3D models, GIS and Digital Imaging Tools—are being employed during post-excavation analysis (e.g. in stratigraphic analysis) and how these are integrated with other more conventional data types (e.g. forms, sketches, drawings and compiled datasets). We invite papers that explore the challenges of managing these hybrid systems, with particular emphasis on how teams adapt to the evolving demands of digital archaeology and their implications on our knowledge creation and understanding of the past.

How well do digital tools integrate with established archaeological practices during post-excavation? Do they improve research outcomes in analysis and interpretation, or do they create new challenges and frictions after fieldwork? How do digital tools align with broader archaeological research aims when applied in post-excavation processes? Digital methods are often seen as an enhancement to traditional workflows, but are they always well-integrated into post-excavation research design? Or do they still risk becoming isolated technical exercises with little analytical impact? And, as the challenge of long-term preservation looms large, and given that digital datasets are prone to obsolescence, how do digital approaches affect the interpretive strategies and post-fieldwork use, dissemination, and long-term preservation of archaeological data? What are your best practices for sharing digital data, particularly after excavation, from engaging the public through interactive 3D models to balancing digital methods with traditional dissemination approaches? Do you have ‘success’ stories or even ‘glorious failures’ to share?

We therefore welcome papers discussing experiences from the integration of digital tools within larger research frameworks, particularly in terms of how they interact with ‘established’ or ‘traditional’ archaeological methods during post-excavation processes, and addressing the methodological implications of using these digital tools in the analysis, interpretation, and dissemination of archaeological knowledge. We acknowledge that the degree of digital integration varies significantly depending on local traditions, funding, and institutional support as well as between research, curatorial and commercial contexts. We hope that this session can take advantage of the international community of CAA to shine a light upon the global variability in the adoption of digital tools across different regions. We encourage comparative studies that highlight how these factors shape archaeological practice and the balance between digital and analog approaches.

Thus we invite papers on the following topics:

  • The application of digital data in post-acquisition analysis and its impact on traditional archaeological workflows.
  • The methodological integration of digital tools into broader research aims, and how they interact with traditional methods.
  • Workflow management in hybrid digital-traditional systems, and the human and technical challenges in maintaining these workflows.
  • Strategies for disseminating digital archaeological data to both academic and public audiences, and the role of platforms in making these datasets accessible.
  • Institutional approaches to the long-term preservation of hybrid and digital data, including quality control and the risks of obsolescence.
  • Comparative insights into the global variability of digital post-excavation processes in archaeology, shaped by local traditions, funding, and policies.

This session will follow a standard format with a series of 20-minute presentations, followed by a panel discussion to encourage dialogue between participants.

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S22: Embracing Digital Ethics: practical applications of ethical frameworks in digital archaeology

Session Organisers:
Alicia Walsh, University of Amsterdam
Hayley Mickleburgh, University of Amsterdam
Paula Granados Garcia, British Museum
Eduardo Herrera Malatesta, Leiden University

Description

Session Format: Standard

The evolving landscape of technology and research brings forth new challenges and ethical considerations within the field of digital archaeology. The accessibility of new technological developments specifically in the field of digitisation has shifted the overarching question from ‘can I?’ to ‘should I?’ The London Charter, the FAIR and CARE principles, and the CAA ethics policy have been guiding researchers in navigating the complexities of our work, yet there is still a lack of concrete policies guiding the ethical implementation and use of technology in the workplace (Riso et al. 2023, Rouhani, 2023). On one hand, the flexibility of the ethical policies that do exist makes them applicable to varied and differing scenarios. On the other hand, this same flexibility and generalisation can make it harder to tailor them into the specifics of the daily practice. Ethics committees granting research approval tend to focus on legal compliance (Dennis, 2020), such as GDPR and privacy concerns, making it an obligatory box to be checked instead of a starting point for fruitful discussions on the ethics of digital archaeology. Such discussions include the digital divide (in terms of both technical and geographical barriers), open access to culturally sensitive data, the digitization of human remains, the environmental footprint, or the use of software’s developed amidst geopolitical conflicts. How do we tackle specific challenges within an inclusive framework without adopting a reductionist approach (Rouhani, 2023)? What are some creative on-the-ground approaches to ethical considerations that are encountered within a project, or institution beyond policies and guidelines, which need constant updating and rarely satisfy each person or situation? The issue of how to apply ethical principles is also visible in other fields of archaeology, beyond the digital. The Society for American Archaeology sets out nine ethical principles for which archaeologists should strive to meet. However, they recognise that some principles may be impossible to meet or may conflict (SAA, 2024). There is a need to engage with other ethical debates and discussion in archaeology, many of which are at a more advanced stage than where digital archaeology currently finds itself. Restitution, equitable access, intellectual property, the public display of artifacts (Gazi, 2014) and working in (post)conflict zones (Newson and Young, 2022) are just a few examples of current debates, many of which may become more nuanced once technologies are incorporated. Looking at how archaeologists are practically engaging with ethical dilemmas and frameworks may help us improve the way we approach ethics within digital archaeology. This session will discuss the necessity of ethical frameworks in guiding the development, implementation, and use of technology. It will address the creation of such frameworks and their practical applications on a project and institutional level. We will also take a critical look at policy documents and guidelines while discussing how to approach the future of ethics in our field. Such projects may include questions of ownership, conflicted heritage, environmental sustainability, and disability access to archaeology, using digital methods such as (but not limited to) 3D documentation, virtual and augmented realities, artificial intelligence, or remote sensing. By examining these issues within and outside digital archaeology, participants may gain a deeper understanding of the ethical challenges that arise in our field and how they may be addressed and embraced.

References

Dennis, L. M. 2020. Digital Archaeological Ethics: Successes and Failures in Disciplinary Attention. JCAA, Vol 3, No 1. https://journal.caa-international.org/articles/10.5334/jcaa.24

Gazi, A. 2014. Exhibition Ethics – An Overview of Major Issues. Journal of Conservation and Museum Studies. Vol. 12, No. 1. https://doi.org/10.5334/jcms.1021213

Newson P, Young R. Post-conflict ethics, archaeology and archaeological heritage: a call for discussion. Archaeological Dialogues. 2022;29(2):155-171. https://doi.org/10.1017/S1380203822000253

Riso, S., Adăscăliței, D. and Contreras, R. R. 2023. Ethical digitalisation at work: From theory to practice. Publications Office of the European Union, Luxembourg. https://www.eurofound.europa.eu/en/publications/2023/ethical-digitalisation-work-theory-practice

Rouhani, B. 2023. Ethically Digital: Contested Cultural Heritage in Digital Context. SDH, Vol 7, No 1, 1-16. https://doi.org/10.14434/sdh.v7i1.35741

Society for American Archaeology. 2024. SAA Principles of Archaeological Ethics. https://www.saa.org/career-practice/ethics-in-archaeology

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S23: New Frontiers in Drone Applications

Session Organisers:
Jitte Waagen,University of Amsterdam
Matthias Lang, Universität Bonn
Manuel Peters, Max Planck Institute of Geoanthropology 
Mason Scholte, University of Amsterdam

Session Format: Standard

Description

This session invites contributions from the field of drone applications in field archaeology that go beyond by now well-established practices such as drone photogrammetry as a means of archaeological mapping and documentation. In the last decade, field archaeology has seen the rapid rise of remotely piloted aircraft with multirotor and fixed wing platforms and sensors becoming increasingly affordable and easier to operate. Drone platforms are part of the remote sensing spectrum but occupy their own specific application niche due to their unique capabilities with regard to sensor deployment, flexible operation, (extreme) high resolutions, etc. Although their potential has been showcased frequently in different studies, and for example small drones have by now become a common instrument in the field archaeologists’ toolbox, there is still much to be explored. For example, various sensor types are still rarely used to their full potential – although examples exist (e.g. Lang et al 2016, Waagen et al 2022) – such as hyperspectral cameras, thermal cameras, or LiDAR sensors, let alone traditional geophysical sensors such as drone-based GPR. Not only is there much more to understand about their potential application in different geographical environments, also the exact procedures for deployment and data analysis would benefit from improvement and transparency. Also, application of drone remote sensing as a tool in different archaeological contexts, such as excavations, is only starting to appear, and great benefit can be expected from the integration of AI/ML-supported methodologies for data collection and analysis workflows. But apart from technological innovation, the field of drone applications has yet to mature in different aspects; a challenge for example is to develop well-considered integrative and multidisciplinary approaches to a broader landscape archaeological research approach but also to develop FAIR documentation workflows and procedures (cf. Lozić, Edisa & Štular 2021). In this session, we welcome papers that showcase and evaluate novel developments with regards, but not exclusive, to:

  • Modalities and scales of drone deployment
  • Comparative sensor performance studies in different environments
  • FAIR documentation workflows/procedures
  • Advanced drone sensor applications, e.g. hyperspectral, thermal, LiDAR, magnetometry, GPR, etc.
  • Application contexts, e.g. remote sensing over excavations
  • Workflows and analytical procedures, incl. AI/ML approaches
  • Integrative multidisciplinary approaches, e.g. drone remote sensing with soil analysis/vegetation studies

In addition to presentations showcasing case studies and workflows related to drones, we also welcome papers on other types of autonomous vehicles dealing with these issues.

References

Lang – T. Behrens – K. Schmidt – D. Svoboda – C. Schmidt, A Fully Integrated UAV System for Semi-Automated Archaeological Prospection, in: Proceedings of the 43rd Annual Conference on Computer Applications and Quantitative Methods in Archaeology edited by S. Campana, R. Scopigno, G. Carpentiero and M. Cirillo (2016) 989-996

Lozić, Edisa & Štular, Benjamin. (2021). Documentation of Archaeology-Specific Workflow for Airborne LiDAR Data Processing. Geosciences. 11. 26. 10.3390/geosciences11010026.

Waagen, J.; Sánchez, J.G.; van der Heiden, M.; Kuiters, A.; Lulof, P. In the Heat of the Night: Comparative Assessment of Drone Thermography at the Archaeological Sites of Acquarossa, Italy, and Siegerswoude, The Netherlands. Drones 2022, 6, 165. https://doi.org/10.3390/drones6070165

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S24: Digital Fieldwork Documentation in Archaeology: Innovations, Challenges and Standards

Session Organisers:
Quentin DRILLAT, Éveha International / Ghent University
Killian REGNIER, FNRS Research Fellow, Université catholique de Louvain/Université Claude Bernard Lyon I

Description

Session Format: Standard

Digital technologies have deeply permeated the many layers of archaeology, leading to its profound reshaping. The very first step of the archaeological practice, namely field data collection, is also increasingly transitioning from traditional paper-based records to digital recording (Roosevelt et al. 2015). This session focuses on current data collection practices in archaeology, highlighting innovative strategies, challenges, and emerging trends. It aims to open a discussion on best practices appearing in the different specialties of field archaeology, from excavations to regional surveys and from rescue to research archaeology.

In the context of rescue archaeology, where time constraints and the urgency to salvage information are paramount, digital technologies have facilitated the rapid and accurate documentation of threatened sites, enabling the creation of comprehensive digital records. Various archaeological services have also developed centralized recording systems aimed at standardizing data collection across different projects (Masson-MacLean et al. 2021; Montagnetti and Guarino 2021). Meanwhile, in research archaeology, multiple campaigns are often conducted year after year on the same sites by different teams. In this context, digital native recording provides an opportunity to standardize data (Boyd et al. 2021), in contrast to heterogeneous legacy datasets inherited from pre-digital practices that produced large amounts of paper records, photographs, hand-drawn maps and section drawings, which are often difficult to access or integrate with modern digital datasets.

Archaeological survey is another field practice that strongly benefited from the integration of digital recording on the field. Because it produces large datasets and needs spatial data to be linked to attribute archaeological data, archaeological surveys have been perfect laboratories for developing digital practices linking archaeological records and location data in common databases with the introduction of mobile Geographic Information Systems (Ames et al. 2020; Pažout 2023; Lindsay and Kong 2020; Cascalheira, Bicho, et Gonçalves 2017; Sobotkova et al. 2021). Best digital practices have thus become crucial for maximizing the efficiency, accuracy, and integration of these increasing data types and volumes.

Our first aim is therefore to propose stimulating exchanges around different field recording practices in rescue and research archaeology, as well as in surveys and excavations. We invite papers that present these practices and include reflections on the following themes:

  • Importance of consistent terminologies and standardized data recording practices for efficiency and for ensuring the long-term accessibility and usability of archaeological data.
  • Integrating attribute archaeological data with spatial data and other archaeological information, such as photographs, or 3D models, to create rich and comprehensive datasets.
  • Integration of non-digital-born documentation (section drawings, …)
  • Use of 3D documentation (photogrammetry, laser-scanning, …)
  • Use of mobile GIS or other archaeology-oriented applications in fieldwork practices
  • Data synchronization and saving during fieldwork
  • Costs of digital workflow implementation
  • Future directions in digital fieldwork practices

Contributions may include case studies demonstrating successful – or less successful! – implementations of best practices, innovative solutions for data capture in specific research contexts, and critical evaluations of existing methodologies and emerging digital recording applications. We seek to foster a comprehensive understanding of the evolving best practices for archaeological data collection in a digital world and identify areas for further improvement and development. Submissions from archaeologists of diverse backgrounds are encouraged, as they will enrich this critical conversation and contribute to the advancement of the field.

References

Ames, Christopher J. H., Matthew Shaw, Corey A. O’Driscoll, and Alex Mackay. 2020. « A Multi-User Mobile GIS Solution for Documenting Large Surface Scatters: An Example from the Doring River, South Africa ». Journal of Field Archaeology 45 (6): 394‑412. https://doi.org/10.1080/00934690.2020.1753321.

Boyd, Michael J., Rosie Campbell, Roger C. P. Doonan, Catherine Douglas, Georgios Gavalas, Myrsini Gkouma, Claire Halley, et al. 2021. « Open Area, Open Data: Advances in Reflexive Archaeological Practice ». Journal of Field Archaeology 46 (2): 62‑80. https://doi.org/10.1080/00934690.2020.1859780.

Cascalheira, João, Nuno Bicho, and Célia Gonçalves. 2017. « A Google-Based Freeware Solution for Archaeological Field Survey and Onsite Artifact Analysis ». Advances in Archaeological Practice 5 (4): 328‑39. https://doi.org/10.1017/aap.2017.21.

Lindsay, Ian, and Ningning Nicole Kong. 2020. « Using the ArcGIS Collector Mobile App for Settlement Survey Data Collection in Armenia ». Advances in Archaeological Practice 8 (4): 322‑36. https://doi.org/10.1017/aap.2020.26.

Masson-MacLean, Edouard, James O’Driscoll, Cathy McIver, and Gordon Noble. 2021. « Digitally Recording Excavations on a Budget: A (Low-Cost) DIY Approach from Scotland ». Journal of Field Archaeology 46 (8): 595‑613. https://doi.org/10.1080/00934690.2021.1970444.

Montagnetti, Roberto, and Giuseppe Guarino. 2021. « From Qgis to Qfield and Vice Versa: How the New Android Application Is Facilitating the Work of the Archaeologist in the Field ». In ArcheoFOSS XIII Workshop—Open Software, Hardware, Processes, Data and Formats in Archaeological Research, 6. MDPI. https://doi.org/10.3390/environsciproc2021010006.

Pažout, Adam. 2023. « Evaluating QField as a Mobile GIS Solution for Archaeological Survey ». In Human History and Digital Future : Proceedings of the 46th Annual Conference on Computer Applications and Quantitative Methods in Archaeology, édité par Matthias Lang, Volker Hochschild, et Till Sonnemann, 161‑70. Tübingen: Tübingen University Press.

Roosevelt, Christopher H., Peter Cobb, Emanuel Moss, Brandon R. Olson, and Sinan Ünlüsoy. 2015. « Excavation Is Destruction Digitization: Advances in Archaeological Practice ». Journal of Field Archaeology 40 (3): 325‑46. https://doi.org/10.1179/2042458215Y.0000000004.

Sobotkova, Adela, Shawn A. Ross, Petra Hermankova, Susan Lupack, Christian Nassif-Haynes, Brian Ballsun-Stanton, and Panagiota Kasimi. 2021. « Deploying an Offline, Multi-User, Mobile System for Digital Recording in the Perachora Peninsula, Greece ». Journal of Field Archaeology 46 (8): 571‑94. https://doi.org/10.1080/00934690.2021.1969837

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S25: Looking for Wooden Architecture in Post Holes Constellations: Computational Approaches, Methods, and Tools to Reveal the Invisible

Session Organisers:
Raphaëlle Javet, University of Zurich
Jonas Blum, University of Zurich
Aurèle Pignolet, InSitu Archéologie SA

Description

Session Format: Standard

Wooden architecture often leaves few traces in archaeology. After a building is abandoned, its superstructure is quickly destroyed, leaving only tenuous remains in the ground, mainly in the form of post holes. Despite the prevalence of posts in construction throughout history, the subtle traces they leave present challenges for in-depth architectural interpretations and structural reconstructions. The preceding research conducted in the fields of ethnoarchaeology and dendroarchaeology has provided valuable insights into the wooden architecture and settlement structures. Nevertheless, the architectural features of buildings with load-bearing posts and other wooden constructions (palisades for instance) remain largely unknown, both for prehistoric societies and historical periods, such as the early European Middle Ages.

This gap in knowledge, primarily due to the discretion of the remains, can also be attributed to a certain paucity of methodological analysis that adequately accounts for the remains of wooden architecture. Reconstructions pertaining to the prehistoric period for instance are still frequently based on simple ethnological comparisons and a contemporary understanding of settlements, rather than on a more rigorous and systematic approach. This gap has also been exacerbated by changes in archaeological data collection methods, especially with the increasing prevalence of preventive archaeology (or rescue/commercial archaeology), which is now ever more systematic in many countries. Preventive archaeology allows for the rapid exploration of large areas, generating massive amounts of data, particularly extensive site plans. These site plans, often densely packed with thousands of post holes over several hectares, are difficult to interpret. This is particularly the case when there is a lack of well-developed stratigraphy, or when the area has undergone multiple successive occupations. This complexity makes the architectural analysis of these ‘palimpsest’ sites highly challenging, if not impossible, thus limiting post-excavation studies and the value of resulting publications.

As early as the 1980s, British researchers envisioned computer solutions to help identify coherent patterns of post holes (alignments, arcs). Unfortunately, at the time, due to the lack of sufficient computational capacity to implement and apply the proposed mathematical formulas, the development of tools in this field did not progress. Today, advancements in computational tools, such as shape fitting and pattern recognition, could offer promising solutions to assist the human eye in identifying coherent networks of post holes, leading to the reconstruction of building plans or settlement structures. Such approaches could also be considered for pile fields in the context of wetland settlement (pile dwellings) archaeology and dendroarchaeology.

We invite researchers working on methods and tools to assist in the recognition of coherent patterns of architectural structures on archaeological site plans – particularly post holes and pile – to present their approaches and work, whether they are in the conceptual stage, under development, or already operational. More generally about the issues of post plans, we invite researchers with a focus on the following topics: shape fitting, pattern recognition applied on post plans, AI or Machine learning tools that allow the analysis of post plans, case studies facing problems with post plan interpretation, studies covering the documentation and recording techniques of post holes, theoretical studies covering past and future of the analysis of post plans, etc. Researchers working in the field of dendroarchaeology are also invited to present their views on the issue of architectural reconstructions and the methodological challenges they face. Works concerning all archaeological periods and any region are welcome.

References

Bradley, R., and Small Ch. (1985). « Looking for circular structures in post hole distributions: Quantitative analysis of two settlements from bronze age England ». Journal of Archaeological Science 12 (4): 285‑97.

Cogbill, S. (1980). « Computer Post-Hole Analysis with Reference to the British Bronze Age ». In Laflin, S. (ed.), Computer Applications in Archaeology, 35‑38. Birmingham: Computer Centre, University of Birmingham.

Gates, J. (1986). « Measures and tests of alignment ». Biometrika 73 (3): 731‑34.

Small, Ch. (1988). « Techniques of Shape Analysis on Sets of Points ». International Statistical Review / Revue Internationale de Statistique 56 (3): 243‑57.

Trebsche, P. (2018). « Der Siedlungsplan als archäologisches Palimpsest. Eine Methode zur Datierung von Pfostenbauten in mehrperiodigen Siedlungen ». Archaeologia Austriaca, no 102, 11‑53. https://doi.org/10.1553/archaeologia102s11

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S26: Bridging Non-Invasive and Invasive Archaeology. Developing Computational Tools for Integration, Archiving, Visualisation and Analysis of Multifaceted Datasets

Session Organisers:
Piotr Wroniecki, Montefortino Prospection & Digitalisation
Kamil Niedziółka, University of Gdańsk
Gábor Mesterházy, Hungarian National Museum – National Institute  of Archaeology

Description

Session Format: Standard

This session aims to present ideas, programs, and tools designed to advance the processing and application of non-invasive (geophysics, LiDAR, remote sensing, field-walking etc…) and invasive data in research and rescue archaeology. We focus on their integration into excavation planning, interpretation, and post-processing, with special emphasis on comparative analysis between various datasets. The session encourages contributions that explore:

  • Integrating diverse datasets into excavation planning, interpretation, and post-processing
  • Applying machine learning to archaeological data analysis and management
  • Developing systematic, quantitative methods to evaluate non-invasive techniques in archaeology
  • Proposing new methodologies for comparing excavation data with non-invasive datasets
  • Addressing challenges in managing and analyzing large-scale archaeological datasets
  • Statistical and numerical approaches for dataset comparison and integration
  • Machine learning applications in data sorting, retrieval, classification, and anomaly detection
  • Addressing challenges in managing and analyzing large-scale archaeological datasets
  • Innovative data presentation and visualization techniques

A key focus is to move beyond traditional visual and intuition-based assessments towards more statistical and numerical approaches in evaluating excavation data in relation to non-invasive datasets. We seek papers that propose new methodologies for scientifically comparing and integrating these diverse data types, offering efficient ways to gain insights into how they can enhance the archaeological process. As archaeology grapples with increasingly vast datasets generated by modern prospection and documentation techniques, we also welcome submissions addressing the challenges of data management. This includes exploring tools or solutions for efficient storage, categorization, and retrieval of large collections of digital imagery and other data types. Machine learning approaches to data sorting, retrieval, classification, and anomaly detection are of particular interest. Whether presenting practical completed projects or more theoretical forward-thinking concepts, this session aims to continue the discussion on data integration in archaeology. Our goal is to bridge the gap between non-invasive and invasive archaeological methods that exists often due to lack of concepts or tools that would help bridge this divide.

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S27: Release the Kraken – Mobile GIS empowering survey communities across the globe

Session Organisers:
Julia Chyla, University of Warsaw
Giuseppe Prospero Ciriglliano, Scuola IMT Alti Studi Lucca
Nazarij Buławka, Catalan Institute of Classical Archaeology; University of Warsaw
Adéla Sobotkova, Aarhus Universitet

Description

Session Format: Other

Over the past decades, archaeological field surveys have significantly refined and adapted methodologies to suit various global contexts, from the Mediterranean and Near East to the Americas (Alcock and Cherry 2004; Bintliff, Howard, and Snodgrass 1999; Athanassopoulos and Wandsnider 2011; Banning 2002). In addition to the specific characteristics of each context, it is essential to reflect on the tools and techniques employed and how they are integrated into investigative methodologies. We can observe a gradual change from the site-oriented prospection into a more holistic approach, considering extended artifact scatters and the elusive remains of human presence in the landscape (Knodell et al. 2023). A significant focus was mapping the density of archaeological material between sites using systematic sampling or transects (Judge 1981; Binford 1975; Nance 1983).

The integration of platforms, tools, unmanned aerial vehicles (drones) and artificial intelligence (AI) allows for multi-scale analysis, producing significant results through the possibility to analyze both the quantitative and qualitative dimensions of archaeological data. These advancements enable researchers to better understand the relationship between different layers of information, leading to new insights into landscape archaeology and the complexities of past human-environment interactions. A pressing issue in archaeological surveys is the impact of intensive land use over time, which has led to the depletion of visible archaeological records on the surface. On the other hand, forested areas present unique challenges, as these environments—where archaeological remains might be better preserved—still lack optimized survey strategies (Mazzacca et al. 2022). As field conditions evolve, so too must our methodologies, adapting to account for both degraded landscapes and new technologies that open up a wide range of possibilities.

The GNSS technologies and the expansion of portable handheld devices led to the development of what is currently known as Mobile GIS (Tripcevich 2004; Chyla and Buławka 2020; Sobotkova et al. 2015). It can be used for personal or collaborative work such as recording, monitoring, management, field verification, reporting, and didactics, which empowered archaeologists and cultural heritage authorities (Tibesasa 2021; Anbaroğlu et al. 2020; Abbas et al. 2023). It also changed the surface survey workflows and made systematic sampling or transects simpler and more accessible.

This CAA Mobile GIS Special Interest Group meeting intends to create an environment for presenting and discussing the current projects. It focuses on the extended use of Mobile GIS integrated with other platforms and tools for mapping and monitoring sites, artifacts, and other types of tangible and intangible heritage. In this meeting, we aim to explore the following questions: What changes, benefits, or challenges has mobile technology brought to the overall field workflow? How has it impacted the data lifecycle and research publication or reporting process? How can Mobile GIS impact and empower communities of archaeologists from different countries and continents? How the Mobile GIS can protect heritage and mitigate its destruction or looting?

The session welcomes papers devoted to:

  • field surveys,
  • recording, monitoring, management, field verification and reporting using portable devices,
  • Mobile GIS,
  • settlement analysis,
  • citizen science,
  • surveying in the forest,
  • public archaeology.

Other Format Description

The session will contain 20-minute presentations and will be followed by a discussion block.

References

Zotero link for references: https://www.zotero.org/google-docs/?CSj0kS

Abbas, Riza, Sitaram Toraskar, Sanjay Exambekar, Emilia Smagur, V Shobha, and Andrzej Romanowski. 2023. ‘Geoarchaeological Investigations in and around the Ancient Port Site of Nalasopara: A Preliminary Study’. Studies in India 3 (1): 53–90.

Alcock, Susan E., and John F. Cherry. 2004. Side-by-Side Survey: Comparative Regional Studies in the Mediterranean World. New York. Oxbow Books. http://books.google.com/books?id=8YmBAAAAMAAJ&pgis=1.

Anbaroğlu, B., İ. B. Coşkun, M. A. Brovelli, T. Obukhov, and S. Coetzee. 2020. ‘Educational Material Development on Mobile Spatial Data Collection Using Open Source Geospatial Technologies’. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2020:221–27. https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-221-2020.

Athanassopoulos, Effie F., and LuAnn Wandsnide. 2011. ‘Mediterranean Landscape Archaeology Past and Present’. In Mediterranean Archaeological Landscapes: Current Issues, edited by Effie F. Athanassopoulos and Luann Wandsnider, 1–14. Philadelphia, PA: University of Pennsylvania Press, Inc.

Banning, Edward B. 2002. Archaeological Survey. New York: Kluwer Academic Press.

Binford, Lewis R. 1975. ‘Sampling, Judgement, and the Archaeological Record’. In Sampling in Archaeology, edited by W. J. Mueller, 251–57. Tucson: University of Arizona Press.

Bintliff, John L., Phil Howard, and Anthony Snodgrass. 1999. ‘The Hidden Landscape of Prehistoric Greece’. Journal of Mediterranean Archaeology 12 (2): 139–68.

Chyla, Julia Maria, and Nazarij Buławka. 2020. ‘Mobile GIS – Current Possibilities, Future Needs. Position Paper’. In Digital Archaeologies, Material Worlds (Past and Present). Proceedings of the 45th Annual Conference on Computer Applications and Quantitative Methods in Archaeology, edited by Jeffrey B. Glover, Jessica Moss, and Dominique Rissolo, 99–113. Tübingen: Tübingen University Press. https://doi.org/10.15496/publikation-43226.

Judge, W.J. 1981. ‘Transect Sampling in Chaco Canyon – Evaluation of a Survey Technique’. In Archaeological Surveys of Chaco Canyon, New Mexico, edited by Alden C. Hayes, David M. Brugge, and James W. Judge, 107–37. Publications in Archaeology, 18A. Washington, D.C: U.S. Department of the Interior, National Park Service.

Knodell, Alex R., Toby C. Wilkinson, Thomas P. Leppard, and Hector A. Orengo. 2023. ‘Survey Archaeology in the Mediterranean World: Regional Traditions and Contributions to Long-Term History’. Journal of Archaeological Research 31 (2): 263–329. https://doi.org/10.1007/s10814-022-09175-7.

Mazzacca, G., Grilli, E., Cirigliano, G. P., Remondino, F., & Campana, S. (2022). Seeing among foliage with LIDAR and machine learning: towards a transferable archaeological pipeline; International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences,46, 365-372.

Nance, Jack D. 1983. ‘Regional Sampling in Archaeological Survey: The Statistical Perspective’. Advances in Archaeological Method and Theory 6:289–356.

Sobotkova, Adela, Brian Ballsun-Stanton, Shawn Ross, and Penny Crook. 2015. ‘Arbitrary Offline Data Capture on All of Your Androids: The FAIMS Mobile Platform’. In Across Space and Time : Papers from the 41st Conference on Computer Applications and Quantitative Methods in Archaeology : Perth, 25-28 March 2013, 80–88. Amsterdam: Amsterdam University Press. http://en.aup.nl/books/9789089647153-across-space-and-time.html.

Tibesasa, Ruth. 2021. ‘An Archaeological Study of Farming Communities on the Northern Shores of Lake Victoria Nyanza, Uganda’. Doctoral thesis, Pretoria: University of Pretoria (South Africa).

Tripcevich, Nicholas. 2004. ‘Flexibility by Design: How Mobile GIS Meets the Needs of Archaeological Survey’. Cartography and Geographic Information Science 31 (3): 137–51.

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S28: Follow Rivers: the application of advanced remote sensing, machine learning and modelling in the studies of water management of past societies

Session Organisers:
Arciero, Roberto, University of Leiden
Nazarij Buławka, Catalan Institute of Classical Archaeology; University of Warsaw
Arnau Garcia-Molsosa, Catalan Institute of Classical Archaeology
Navjot Kour, Catalan Institute of Classical Archaeology

Description

Session Format: Standard

Studies related to ancient water management are particularly relevant to modern environmental problems and are central to the discourse of complex societies. Wittfogel’s hydraulic hypothesis (1955; 1957) provoked early archaeological studies to investigate the link between extensive irrigation systems and the centralised authority of early states. While present-day research emphasises the significance of water management, it also indicates a more complicated picture (Rost 2022; Wilkinson, Rayne, and Jotheri 2015). Mesopotamian examples indicate that irrigation developed gradually from cleaning parts of the crevasse splay into an extensive network of canals (Wilkinson and Hritz 2013). On the other hand, in the Indus Civilisation, irrigation was not necessary because agriculture was based on the monsoon cycle (Madella and Lancelotti 2022), while in southern Turkmenistan (Central Asia) canals for irrigation were already in place during the Chalcolithic period (Lisitsina 1969).

Water management is a highly complex research field requiring collaboration between different disciplines and the use of various methods. The irrigation landscape is palimpsest, and it can consist of canals, qanats, natural or partially modified channels, rivers, and streams from different periods (Jotheri 2018). The ancient landscape continuously evolves through human agency and natural processes, which leads to deleting or masking of the features (Wilkinson 2003). Computational methods, specifically when combined with other techniques in landscape archaeology, allow us to understand some of that complexity (Garcia et al. 2019). Recent computational method developments have changed how we study ancient landscapes. The appearance of a vast battery of high-resolution satellite images, including HEXAGON (Hammer, FitzPatrick, and Ur 2022), drone imagery (Campana 2017), newly available digital surface models (González et al. 2020), and large cloud datasets available in Google Earth Engine (Orengo and Petrie 2017), opened avenues for reconstructing irrigation systems with greater temporal and spatial resolution. Predictive or agent-based modelling offers another option to build hypotheses on past land use (Angourakis et al. 2014). While machine learning and deep learning provide much for the study, their application is still limited (Li et al. 2022). The session aims to bring together researchers attempting novel approaches in water management studies using computational methods. It welcomes papers focused on satellite remote sensing, Google Earth Engine, machine learning and deep learning, predictive or agent-based modelling of irrigation systems, detection or spatial analysis, and landscape evolution.

References

Zotero link for references: https://www.zotero.org/google-docs/?WmxOJN

Angourakis, Andreas, Bernardo Rondelli, Sebastian Stride, Xavier Rubio-Campillo, Andrea L. Balbo, Alexis Torrano, Verònica Martinez, Marco Madella, and Josep M. Gurt. 2014. ‘Land Use Patterns in Central Asia. Step 1: The Musical Chairs Model’. Journal of Archaeological Method and Theory 21 (2): 405–25. https://doi.org/10.1007/s10816-013-9197-0.

Campana, Stefano. 2017. ‘Drones in Archaeology. State-of-the-Art and Future Perspectives’. Archaeological Prospection 24 (4). https://doi.org/10.1002/arp.1569.

Garcia, Arnau, Hector Orengo, Francesc Conesa, Adam Green, and Cameron Petrie. 2019. ‘Remote Sensing and Historical Morphodynamics of Alluvial Plains. The 1909 Indus Flood and the City of Dera Ghazi Khan (Province of Punjab, Pakistan)’. Geosciences 9 (1): 21. https://doi.org/10.3390/geosciences9010021.

González, Carolina, Markus Bachmann, José-Luis Bueso-Bello, Paola Rizzoli, and Manfred Zink. 2020. ‘A Fully Automatic Algorithm for Editing the TanDEM-X Global DEM’. Remote Sensing 12 (23): 3961. https://doi.org/10.3390/rs12233961.

Hammer, Emily, Mackinley FitzPatrick, and Jason Ur. 2022. ‘Succeeding CORONA: Declassified HEXAGON Intelligence Imagery for Archaeological and Historical Research’. Antiquity 96 (387): 679–95.

Jotheri, Jaafar. 2018. ‘Recognition Criteria for Canals and Rivers in the Mesopotamian Floodplain’. In Water Societies and Technologies from the Past and Present, edited by Yijie Zhuang and Mark Altaweel, 111–26. UCL Press. https://doi.org/10.2307/j.ctv550c6p.12.

Li, Qian, Huadong Guo, Lei Luo, and Xinyuan Wang. 2022. ‘Automatic Mapping of Karez in Turpan Basin Based on Google Earth Images and the YOLOv5 Model’. Remote Sensing 14 (14): 3318. https://doi.org/10.3390/rs14143318.

Lisitsina, Gorislava Nikolaevna. 1969. ‘The Earliest Irrigation in Turkmenia’. Antiquity 43 (172): 279–88, pl. XXXIX.

Madella, Marco, and Carla Lancelotti. 2022. ‘Archaeobotanical Perspectives on Water Supply and Water Management in the Indus Valley Civilization’. In Irrigation in Early States New Directions, 113–36. Chicago: Oriental Institute of the University of Chicago.

Rost, Stephanie. 2022. ‘Introduction’. In Irrigation in Early States New Directions, edited by Stephanie Rost, xi–xxx. Chicago: Oriental Institute of the University of Chicago.

Wilkinson, Tony James. 2003. ‘Landscape of Irrigation’. In Archaeological Landscapes of the Near East, 71–99. Tucson: University of Arizona Press.

Wilkinson, Tony James, and Carrie Hritz. 2013. ‘Physical Geography, Environmental Change and the Role of Water’. In Models of Mesopotamian Landscapes: How Small-Scale Processes Contributed to the Growth of Early Civilizations, 1–34. Archaeopress Oxford, UK.

Wilkinson, Tony James, Louise Rayne, and Jaafar Jotheri. 2015. ‘Hydraulic Landscapes in Mesopotamia: The Role of Human Niche Construction’. Water History 7 (4): 397–418. https://doi.org/10.1007/s12685-015-0127-9.

Wittfogel, Karl August. 1955. ‘Developmental Aspects of Hydraulic Societies’. Irrigation Civilizations: A Comparative Study, 43–53.

———. 1957. Oriental Despotism; a Comparative Study of Total Power. New Haven: Yale University Press.

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S29: Heritage under bombs – digital methods in the studies of endangered heritage in conflict zones

Session Organisers:
Nazarij Buławka, Catalan Institute of Classical Archaeology; University of Warsaw
Stefano Campana, University of Siena
Mariusz Drzewiecki, University of Warsaw
Oleksandra Ivanova, National University of Kyiv-Mohyla Academy

Description

Session Format: Other

In the recent few years, the political situation across Ukraine, Sudan, Syria, Levant, Central African Republic, Afghanistan, Manipur (India), Georgia, and many other places in the globe poses a critical threat to the preservation of tangible and intangible heritage (Shydlovskyi et al. 2023; Shydlovskyi, Telizhenko, and Ivakin 2023; Ahmad 2022). This includes destruction, bombing, usage for military activity or looting. The war in Ukraine and the Middle East crisis show that heritage became not only a silent victim of conflict but also a tool for whitewashing military actions towards civilians. Looted artifacts, in turn, often end up on the market, and the revenue helps to finance military operations. In early September 2024, shortly before the submission of the session abstract, artifacts from Sudanese museums began appearing on online auctions.

A basic principle in the practice of cultural resource management is that to be effective in protecting and managing any kind of heritage (from small objects to buildings, landscapes and including intangible cultural heritage), knowing what heritage you have is essential to safeguarding it. Even though various institution-led or community-based actions are being taken to document heritage before and after it is destroyed, unfortunately, it vanishes faster than any archaeologist or museologist can work. Therefore, there is a deep necessity for creating and sharing a common methodology for protecting and conserving heritage through digital methods and the ways such digital skills can be transferred/shared with institutions and professionals in regions affected by conflicts. This session intends to bring together researchers from areas affected by conflict and war, specialized in digital methods, and deeply concerned about the future of heritage. The session welcomes papers devoted to monitoring archaeological heritage in conflict zones focused on:

  • inventories and database for heritage preservation;
  • remote sensing (from satellite to unmanned aerial vehicles UAV):
  • photogrammetry and laser scanning;
  • citizen science.

Other Format Description

The session will include regular presentations and a more extended discussion block at the end.

References

Zotero link for references: https://www.zotero.org/google-docs/?sk9ySV

Bevan, R. 2016. The destruction of memory: architecture at war. London: Reaktion.

Campana, S., Sordini, M., Berlioz, S., Vidale, M., Al-Lyla, R., Abbo al-Araj, A., & Bianchi, A. 2022. Remote sensing and ground survey of archaeological damage and destruction at Nineveh during the ISIS occupation. Antiquity, 1-19, https://doi.org/10.15184/aqy.2022.14

 Casana J., 2015. The Cultural Heritage Crisis in the Middle East, Vol. 78, No. 3, Special Issue. Casana, J. & E.J. Laugier. 2017. Satellite imagery-based monitoring of archaeological site damage in the Syrian civil war. PLoS ONE 12: 1–31. https://doi.org/10.1371/journal.pone.0188589

Newson P., Young R., 2018. Post-conflict archaeology and cultural heritage rebuilding knowledge, memory and community from war-damaged material culture, New York, Routledge.

 Ahmad, Rukhsar. 2022. ‘The Legal Role of Government in Protecting Cultural Heritage and Archaeological Sites in the War-Affected Countries: The Case of Iraq and Syria’. Journal of Liberty and International Affairs 8 (2): 281–92.

Shydlovskyi, Pavlo S., Ian Kuijt, Viacheslav Skorokhod, Ivan Zotsenko, Vsevolod Ivakin, William Donaruma, and Sean Field. 2023. ‘The Tools of War: Conflict and the Destruction of Ukrainian Cultural Heritage’. Antiquity 97 (396): e36. https://doi.org/10.15184/aqy.2023.159.

Shydlovskyi, Pavlo S., Serhii A. Telizhenko, and Vsevolod H. Ivakin. 2023. ‘Archaeological Monitoring in War-Torn Ukraine’. The Historic Environment: Policy & Practice 14 (2): 154–80. https://doi.org/10.1080/17567505.2023.2209835.

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S30: Advancing Open Science Practices in Archaeology: Linking Data Principles, Stewardship, and Digital Infrastructures

Session Organisers:
Angeliki Tzouganatou, OpenAIRE
Markos Katsianis, University of Patras
Despoina Tsiafaki, Athena Research Center
Elli Papadopoulou, Athena Research Center

Description

Session Format: Standard

Open Science, with its commitment to transparency, collaboration, and accessibility, alongside the development of open infrastructures, offers a transformative approach to documenting and managing archaeological data. The FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles have been instrumental in establishing a clear path for data stewardship, significantly advancing the management, dissemination, and utilization of scientific data (Wilkinson et al. 2016).

In addition to FAIR, several other frameworks address different facets of digital data management. The CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles, for instance, emphasize the ethical, cultural, and social dimensions necessary for managing archaeological data in a way that is equitable, inclusive, and responsive to the needs of all stakeholders, particularly Indigenous and local communities (Carroll et al. 2021). The London Charter advocates for intellectual transparency and qualitative metadata, emphasizing the importance of clear distinctions between evidence and interpretation (Watterson 2015). Meanwhile, the growing emphasis on paradata focuses on documenting methodologies, decision-making processes, and interpretive steps, which are essential for improving the reliability and transparency of archaeological research (Huvila 2022). Several other principles and collective research initiatives, ranging from data interoperability to method transparency and ethical concerns, also support the broader goals of Open Science.

Digital infrastructures, such as OpenAIRE, are crucial in the Open Science movement by providing services and expertise that advance the European Open Science Cloud (EOSC) and support the broader implementation of FAIR principles across Europe. Digital infrastructures are not merely repositories for data but key actors in shaping and regulating the emerging digital processes that increasingly define archaeological practice. In a sense, all archaeological fieldwork is expected to meet the standards set by these infrastructures, as they serve as the final destination for the resulting digital data. While significant effort has been devoted to developing the technical aspects of these infrastructures and establishing quality control mechanisms, such as accreditation processes, there has been less critical reflection on the potential constraints and implications they may impose on archaeological practices (Huggett 2024).

Several key questions arise in this evolving landscape. How aware is the archaeological community of Open Science practices, and how feasible is it to implement these principles? What theoretical knowledge and technical skills are required? What types of data, metadata, or paradata are best suited to each goal? Are there tensions or conflicts between different frameworks? Is openness always beneficial, or could it reinforce existing power imbalances or undermine data sovereignty? What measures can digital infrastructures adopt to address such issues along with other ethical or cultural concerns, particularly in the stewardship of archaeological and heritage data? How are these frameworks implemented in the absence of regulatory standards, sufficient repository facilities, or adequate funding? Ultimately, what constraints do these frameworks impose on archaeological research, how do they reshape archaeological knowledge production and heritage management, and what opportunities do they present?

This session aims to critically explore these challenges from both bottom-up (e.g., the archaeologist or the participating community) and top-down (e.g., the data manager or the data curator) perspectives. Despite varying levels of digital integration across global and research contexts, sharing experiences can help better identify the problems, requirements, changes, successes, and failures encountered when implementing Open Science practices in archaeology. We therefore invite submissions that explore these challenges, offer comparative insights into data standardization and requirements for ingestion and deposition in digital infrastructures (such as ARIADNE, DARIAH, OpenAIRE, SSHOC, Parthenos), in line with Open Science principles.

We believe that exchanging experiences will help us understand the practicalities of implementing different aspects of Open Science in archaeology. By integrating these frameworks into digital archaeological research, we can develop a more holistic approach to inclusive data stewardship, transparent knowledge-building practices, and equitable data policy-making. This integration not only complements existing frameworks but could also signal a paradigm shift in the governance, documentation of archaeological data.

References

Carroll, S.R., Herczog, E., Hudson, M. et al. 2021. Operationalizing the CARE and FAIR Principles for Indigenous data futures. Sci Data 8: 108. https://doi.org/10.1038/s41597-021-00892-0

Huggett, J. 2024.Deconstructing the Digital Infrastructures Supporting Archaeological Knowledge, Current Swedish Archaeology, 31: 11–38 https://doi.org/10.37718/CSA.2023.01

Huvila, I. 2022. Improving the usefulness of research data with better paradata, Open Information Science 6: 28-48. https://doi.org/10.1515/opis-2022-0129

Watterson, A. 2015. Beyond Digital Dwelling: Re-thinking Interpretive Visualisation in Archaeology, Open Archaeology, 1. https://doi.org/10.1515/opar-2015-0006 Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. 2016. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018. https://doi.org/10.1038/sdata.2016.18

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S31: New Steps in Computational Methods and Theory to Studying Past Seafaring and Human-Water Interactions

Session Organisers:
Alberto Garcia-Piquer, Autonomous University of Barcelona
Ermioni Vereketi, National and Kapodistrian University of Athens
Emma Slayton, Carnegie Mellon University
Karl Smith, University of Oxford

Description

Session Format: Standard

Water is an element that connects and separates different cultures, civilisations, and political/social entities. It can act as a field for the development of communication networks that facilitate trade and cultural and economic interaction, and also as a border of separation. Although archaeologists have historically tended towards the latter view, there have been numerous calls to rethink the traditional ways in which archaeologists have described the past, and there is a growing interest in boats as technological and social innovations that made much of human history possible. How maritime, riverine, and lacustrine peoples negotiated their watery worlds in the past has become an important and inspiring topic of debate, one that is increasingly opening new views and theoretical horizons (Garcia-Piquer, Fauvelle and Grier 2025). In late prehistoric and early historic periods globally, maritime connectivity favoured the spread of cultural identity and allowed the diffusion of goods, ideas and technologies (Nutall 2021). In this way, trade emerged as a cornerstone of the prosperity of many ancient civilisations, as a wide variety of goods and luxury items travelled vast distances by sea. However, objects did not travel alone; instead, the spread of valuable goods was accompanied by the spread of cultural practices, religious beliefs and other cultural elements (Jarriel 2018; Slayton 2018). This is because movement is not limited to traders alone, but also includes other travelers and artisans who carry their traditions, expertise and culture (Broodbank 2000). These mariners create rich mosaics of cultural exchange and interaction, contributing to the social and cultural dynamics of the communities they visit and inhabit. That is the reason why maritime networks also had important political implications. The control of strategic sea routes and ports was a key factor in shaping and maintaining the balance of power of ancient civilisations. Various empires and city-states sought to dominate these routes to secure economic and military advantages. It is therefore clear that the importance of maritime mobility lies in the dissemination of features that are key elements of later cultural heritage. Regardless of the period, but especially in prehistoric times, the scarcity of direct archaeological evidence makes reconstructing seafaring difficult. Following the lead of experimental reconstruction and navigations, prehistoric and historic seafaring has been a fertile ground for computational simulations during the last decades. Many works have evaluated maritime routes with a wide range of computational methods, from calculating trajectories based on currents and winds (e.g. Montenegro et al. 2006) to least cost paths methods and cost surfaces (e.g. Perttola 2022; McLean and Rubio-Campillo 2022) and agent-based models (e.g. Smith 2020). Frequently focused on early migrations and the colonization of new continents, these simulations have been applied in various parts of the world. However, attempting to reconstruct past seafaring presents major challenges. Beyond the archaeological visibility of watercraft, a key issue is that theoretical models and archaeological predictions concerning aquatic movement are less developed than in terrestrial cases. Despite recent computational and archaeological advances, we are still navigating many uncharted waters. Moreover, a look at the increasing number of models developed in the last few years or currently under development reflects the diversity of methodological and theoretical approaches to human-water relationships. While this diversity is in itself a projection of the multiple dimensions and richness of the topic, we strongly believe that discussion, comparison, and collaboration between world-wide modelers and researchers will bring us to new levels of understanding. Therefore, building on recent efforts to network a community of modelers and researchers interested in the multiple dimensions of seafaring and the transformative capacities of boat technology, we propose a session that brings together researchers from many parts of the world, different study periods and multiple corners of the discussion including computational archaeology, anthropology, oceanography, atmospheric sciences, geography, and computer science. We encourage our colleagues working in this area to submit paper on various aspects of modelling movement across water including (but not limited) to: 1) Designing computational seafaring models and evaluating input and variables. 2) How environment conditions affect seafaring technology and sea routes, and how to go beyond dichotomic views like maritime vs. terrestrial mobility. 3) Investigating the role played by boats and watery connectivity in supporting the emergence and stability of various kinds of social networks in different parts of the world in the past, with a particular interest in the preservation, development and dissemination of cultural elements and behaviours in ancient societies, as well as in the shaping of the cultural map of antiquity. 4) Building from direct experience as well as from ethnographic, historic or archaeological data in indigenous/traditional practices, and ontologies of seafaring to structure computational models. 5) Testing previous computational models in new areas, including the comparison to existing models. 6) How are existing models inspiring the development of new models or methodologies, and better methods of analysing model outputs.

References

Broodbank, C. 2000 An island archaeology of the Early Cyclades. Cambridge University Press, Cambridge.

Garcia-Piquer, A., Fauvelle, M., Grier, C. 2025. Negotiating Watery Worlds: Impacts and Implications of the Use of Watercraft in Small-Scale Societies. University of Florida Press, Gainesville, In press.

Jarriel, K. 2018. Across the Surface of the Sea: Maritime Interaction in the Cycladic Early Bronze Age. Journal of Mediterranean Archaeology 31(1):52-76.

McLean, A., Rubio-Campillo, X. 2022. Beyond Least Cost Paths: Circuit theory, maritime mobility and patterns of urbanism in the Roman Adriatic. Journal of Archaeological Science 138:105534.

Nutall, C. 2021. Seascape Dialogues: Human-Sea interaction in the Aegean from Late Neolithic to Late Bronze Age. PhD thesis, Uppsala University, Uppsala.

Perttola, W. 2022. Digital navigator on the seas of the Selden Map of China: Sequential least-cost path analysis using dynamic wind data. Journal of Archaeological Method and Theory 29(2):688-721.

 Slayton, E. 2018. Seascape Corridors: Modeling routes to connect communities across the Caribbean. Sidestone Press, Leiden.

Smith, K. 2020. Modeling Seafaring in Iron Age Atlantic Europe. PhD thesis, University of Oxford, Oxford.

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S32: Connected Landscapes: Digital and Quantitative Methods for Landscape Archaeology

Session Organisers:
Fernando Moreno-Navarro, Università degli Studi Roma Tre
Emeri Farinetti, Università degli Studi Roma Tre

Description

Session Format: Standard

The integration of digital and quantitative methods in landscape archaeology, while not new, continues to open up new ways of exploring and understanding historical environments. This session aims to provide a space for reflection and debate on the use of advanced technologies in landscape archaeology, such as Geographic Information Systems (GIS) (Conolly & Lake 2006; Farinetti 2011), Network Analysis (NA) (Brughmans & Peeples 2023), or Agent-Based Modelling (ABM) (Romanowska et al. 2021), among others. These tools have revolutionised how archaeologists study human interactions with the natural and built environment, enabling the reconstruction of landscapes, the revelation of hidden connections between settlements, the analysis of trade routes, and the evaluation of how environmental and human factors have shaped the evolution of different territories over time.

Landscape archaeology has focused on understanding how human communities settled, exploited, perceived and transformed space across different historical periods. In this field, GIS allows for the representation and spatial analysis of archaeological data, identifying patterns of occupation, land use, and environmental change (e.g., Grau Mira et al. 2024). Meanwhile, Network Analysis introduces a relational perspective to landscape studies, revealing the connections and flows of goods, people, and ideas between different actors (e.g., De Soto 2019). Agent-Based Modelling (ABM) helps simulate complex scenarios of human interaction, demonstrating how individual and collective decisions might have shaped past landscapes (e.g., Gravel-Miguel & Wren 2018). These methods open new perspectives on how past communities interacted with their environment.

This session invites participants to examine these approaches from different angles, whether in their individual application or in combination within broader analytical frameworks. The goal is to foster an interdisciplinary dialogue that explores the challenges, opportunities, and implications of using these technologies in landscape archaeology research.

We welcome contributions that investigate archaeological landscapes using digital technologies and other innovative quantitative methods, that explore studies on land use and occupation, connectivity and mobility analysis, as well as reconstructions and modelling. We also consider papers that use relational perspectives, such as network analysis, to reveal patterns of interaction between communities, or that combine multiple approaches to offer an integrated view of past landscapes and explore new lines of research.

References

Brughmans, T., & Peeples, M. A. (2023). Network Science in Archaeology. Cambridge University Press. https://doi.org/10.1017/9781009170659

Conolly, J. & Lake, M. (2006). Geographical Information Systems in Archaeology. Cambridge University Press.

De Soto, P. (2019). Network Analysis to model and Analyse Roman Transport and Mobility. Journal of Archaeological Method and Theory, 26(1) 271-289. https://doi.org/10.1007/978-3-030-04576-0_13

Farinetti, E. (2011). Boeotian Landscapes: A GIS-based Study for the Reconstruction and Interpretation of the Archaeological Datasets of Ancient Boeotia. British Archaeological Reports.

Grau Mira, I., Sarabia-Bautista, J., & Narbarte-Hernández, J. (2024). Archaeological landscapes and long-term settlements in the Perputxent valley (eastern Iberia): Exploring land use strategies and sustainability in a Mediterranean mountain area. The Holocene. https://doi.org/10.1177/09596836241259790

Gravel-Miguel, C., & Wren, C. D. (2018). Agent-based least-cost path analysis and the diffusion of Cantabrian Lower Magdalenian engraved scapulae. Journal of Archaeological Science, 99, 1-9. https://doi.org/10.1016/j.jas.2018.08.014

Romanowska, I., Wren, C. D., & Crabtree, S. (2021). Agent-Based Modeling for Archaeology: Simulating the Complexity of Societies. The Santa Fe Institute Press. https://doi.org/10.37911/9781947864382

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S33: Give Your Wikidata Away! A Lightning Talk series followed by a Wikidatathon sharing session

Session Organisers:
Nehemie Strupler, Durham University
Anna Foka, Uppsala University

Description

Session Format: Other

 Linked Open Data is set to become the de facto standard for publishing scientific data, aiming to form a common knowledge base of heterogeneous information. By making scientific data openly available and interoperable, Linked Open Data fosters an Open Science environment that is more inclusive and participatory, enabling scientists from diverse fields to collaborate, share insights, and build upon each other’s work more effectively. The more projects that share the same infrastructure, the denser and more meaningful the entire knowledge graph becomes.

Wikidata’s status as the largest source of Linked Open Data positions it as a hub for linking humanities data across project boundaries. Increasingly, knowledge graphs either import portions of data into Wikidata or propose the creation of property IDs in Wikidata as external identifiers (e.g., P8565 ‘British Museum object ID’ or P9394 ‘Louvre Museum ARK ID’) to point toward other knowledge graphs. This enhances data accessibility and interoperability, including the ability to perform federated queries across multiple databases, which is facilitated by a common basic data model shared via Wikibase. Many different possible uses of Wikidata (the software, the data, and/or the model) are being utilized in the humanities, such as:

  1. Data Enrichment and Linking: Researchers use Wikidata to enrich and connect their datasets with additional information. For example, a project on historical figures can leverage Wikidata to add biographical details, relationships, and links to other relevant entities. This allows for more comprehensive analysis and visualization of interconnected data.
  2. Knowledge Graph Construction, Data Modeling, and Ontology Development: Wikidata’s structured format and intuitive software make it ideal for building knowledge graphs in humanities domains or developing specialized ontologies and data models. Researchers can extract relevant entities and relationships from Wikidata to construct domain-specific graphs for topics like art history, literature, or cultural heritage.
  3. Multilingual Research: As a multilingual resource, Wikidata enables cross-lingual humanities research. Concepts and entities are linked across languages, allowing scholars to explore topics across cultural and linguistic boundaries.
  4. Named Entity Recognition and Linking: Wikidata serves as a valuable reference for named entity recognition and linking in humanities texts. Researchers can use Wikidata’s extensive collection of entities to improve the accuracy of identifying and disambiguating names, places, and concepts in historical documents or literary works.
  5. Querying and Analysis: SPARQL endpoints allow researchers to ask complex questions across vast amounts of humanities-related data. This enables new forms of analysis that blur the boundary between quantitative and qualitative methods.
  6. Data Publication and Sharing: Some humanities projects publish their research outputs directly to Wikidata, contributing to the global knowledge base while making their data openly accessible and reusable by others.

While Wikidata offers significant potential for humanities research, challenges remain. These include addressing data quality issues, overcoming biases in coverage, accommodating different data models (e.g., CIDOC CRM), and developing the skills needed to effectively work with linked data. In this session, we aim to gather people working with, or interested in working with, the Wikidata infrastructure to showcase how they interact with the data, software, or model, and to discuss the challenges they face.

We strongly encourage participants not only to present their projects but also to briefly highlight their workflows, scripts, bots, ideas, and techniques to import, export, enrich, or recognize data that could be further discussed during the Wikidatathon. Following the lightning talks, time will be allocated for a participant-driven session to facilitate collaboration and knowledge sharing. Unlike traditional sessions, this one allows participants to shape the event’s content and structure in real-time. The goal is to foster open discussions, networking, collaboration, and hands-on engagement.

Possible topics include:
  • Advantages and limitations of Wikidata as a central node linked to external sources.
  • Collaborative and asynchronous working.
  • Extraction of statements from a wide range of sources (e.g., bibliographic resources, reports, books, articles, images) and linking them to sources.
  • Extracting data: Automation, such as named entity recognition and disambiguation
  • Designing bots for automation
  • Multilingual data representation.
  • Dealing with contradictory statements.
  • Dealing with other structured data.
  • Dealing with complex issues.
  • Legal and ethical issues for wiki.
  • Data contrôle and source authority
  • SPARQL: difficulties, examples, tutorials, and visualization possibilities.
  • The Wikibase ecosystem: its constant growth, along with good and poor documentation.
  • Using OpenRefine for reconciliation.
  • Leveraging the fully traceable editing history.
  • Sharing data in Wikidata.
  • Potential qualitative and quantitative methods for data analysis.

Other Session Format

The session format will consist of a series of lightning talks (10 minutes each) followed by a hands-on hackathon session. We aim to provide researchers with the opportunity to showcase their work and key takeaways, as well as highlight the most interesting aspects that could be reused, adapted, enriched, or linked by other participants. This session seeks to go beyond a “Bring Your Data” approach to a “Take My Data” approach.

Given that the focus is on the Wikidata infrastructure—emphasizing collaboration and exchange—we are confident that participants will actively engage both in the talks and the hands-on session. Depending on the time available and the number of submissions, we anticipate scheduling approximately 1 hour for talks (4-6 talks) and 45 minutes to 1 hour for the hackathon.

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S34: FAIRification and Standards in Commercial Archaeology

Session Organisers:
Chiara G. M. Girotto, Arch Pro Beratungsgesellschaft mbH
Anna Anzenberger, Illisystems
Gergő Juhász, Lowpoly 360 Kft.
Teodor Muntean, Arch Pro Beratungsgesellschaft mbH

Description

Session Format: Standard

Developer-funded or so called ‘salvage’ archaeology has – in many countries – become one of the main generators of archaeological data. Rescue excavations, especially in the context of large infrastructure projects, have produced tremendous amounts of material heritage. However, national and international excavation and documentation standards established by regional administrations or authorities tend to be highly fractured, individual, and are rarely directly interoperable or comparable. It not only poses difficulties on large scale contextualization but also international cooperation, data sharing, a unified standard for material and cultural heritage as well as sustainable long term data storage and accessibility – not only to research but also the public. Whilst incentives to streamline research data infrastructure in accordance with FAIR principles, have approached these aspects in academic context, their translation to generalized central heritage frameworks, and (national) standards is still in its infancy and sometimes entirely absent. Due to the extensive data output of commercial archaeology reaching a national or even international consensus on the implementation of FAIR data standards in accordance with the respective national laws is not only an essential part of the discipline moving forward but also a move towards a machine-actionable, comparable data space. In this space not only the data but also strategies, digital infrastructure, and workflows become apparent – scientific but also economic decisions shape the approach to heritage data generation and interaction. Due to their cost-effective nature, agility, flexibility, and easy augmentation OpenSource software, individually programmed infrastructure, and code snippets have become essential elements of economic digital data management, swift organization, documentation and report generation in many companies. Commercial archaeology is in the unique position to not only synthesize the interests of different stakeholders, but due to their extensive material and knowledge contribution to be a forerunner in the aforementioned principles for a sustainable future of heritage management and digital data. 

In our session we cordially invite papers addressing software, case studies and the digital infrastructure and workflows of preventive/commercial archaeology and its closely associated disciplines: 

  • Which digital infrastructures have been devised, programmed, and implemented?
  • How can we use our infrastructure to best represent the interest of different stakeholders?
  • Why do we generate the data the way we do?
  • How can the data generated by commercial archaeology become compliant with FAIR[/O] principles?
  • How comparable and interoperable are current national standards?
  • How can we find a common interface with science based archaeology, climate and ecology reconstruction?
  • In the process of FAIRification, generation and adoption of international standards – what is a universal minimal set of metadata?
  • How can we shape the future of digital infrastructure and databases in commercial archaeology?

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S35: Mapping and modelling movement in archaeology: From least cost analysis to diffusion pathways

Session Organisers:
Richard Hewitt, Spanish National Research Council
Manuel Alcaraz-Castaño, University of Alcalá
Mike Morley, Flinders University

Description

Session Format: Standard

Understanding the mobility of past human populations in and around the landscapes they occupied is an enduring challenge that has been addressed at many perspectives and scales. Some approaches, like the wave of advance model (Ammerman and Cavalli-Sforza 1979) or the site catchment modelling approaches of Vita-Finzi et al (1970) predate the application of quantitative methods using modern computers. Others are closely allied to the emergence of geographical information systems (GIS) desktop software in the 1980s and 1990s. For example, there is a large body of work around the concept of “cost”, which concerns the relative difficulty of transit across regions, resource locations or occupation sites, on the basis of physical characteristics like terrain slope, vegetation cover or ocean currents. Least Cost Analysis (LCA), as this is known, is one of the oldest applications of geographical information systems in archaeology and has evolved to become a standard operation undertaken in many contexts and chronological periods. These include exploring the location of Roman roads (Güimil-Fariña and Parcero-Oubiña 2015), understanding connections and tribal territoriality associated with agriculture (Howey 2007), mapping the distribution of Palaeolithic symbolic objects (Gravel Miguel and Wren 2018), or reconstructing historical journeys (Seifried and Gardner 2019), among many others. Agent-based models (ABMs) have been developed that approach the problem through simulation of autonomous decisions around movement under different conditions. For example, Hölzchen et al (2016) propose to evaluate “Out of Africa” hypotheses by modelling the behaviour of individual agents with particular characteristics, e.g. group size, typical interaction range, resource demand, allowing the potential for different hominin species to disperse into different regions to be tested. Some classic models, like the STEPPINGOUT model of Mithen and Reed (2002), approach this question using cellular automata (CA) theory. These authors model population dispersal by dividing the globe into gridded cells and simulating colonization between adjacent cell neighbours. The importance of ease of communication between regions as well as the suitability of the destination territory, included in the concept of “affordances” (Verhagen et al 2019), makes the link between LCA and dispersion models very clear. However, as yet, no coherent “archaeology of movement”, at least in the sense proposed by LLobera (2000), has emerged to unify these different threads. Rather, the range of applications and approaches has expanded within each different knowledge domain, and the boundaries have become increasingly blurred. For example, Lewis (2021) addresses the problem of error in the source elevation data through a Monte Carlo simulation approach that identifies the most probable Least Cost pathways within the stated margin of error. In this sense, Lewis’ probabilistic simulation-based approach links traditional LCA in GIS with least cost models. At the same time, empirical work is becoming more broadly integrative. Bilotti et al’s (2024) highly innovative approach to understanding trade networks in xx moves beyond state-of-the-art by combining both marine and land-based communication networks in a single model. At the same time clear gaps remain, and many problems that have been long exposed remain insufficiently explored or addressed. Classical approaches to LCA based on physical landscape variables may be problematically environmentally deterministic, yet they remain widely used. Some ABM approaches often seem to make little progress beyond the conceptual realm. Human and animal interaction in archaeological models of movement remains under-explored. Finally, artificial Intelligence (AI) is currently receiving enormous attention in every corner of society, yet it’s not clear to what extent it is likely to be useful in archaeological modelling of movement. This session proposes to critically examine quantitative approaches to the archaeology of movement in a broad and integrative way, looking to integrate further these diverse threads and, in so doing, identify differences and commonalities that allow cross-fertilization of ideas beyond domain boundaries. The main objective of the session is to build bridges between case-focussed GIS-based analyses of movement within landscapes and population diffusion models more broadly. In this sense we particularly welcome contributions in the following areas:

  • Explorations of the limits and frontiers of conventional LCA approaches. At what distance and at what scale do ordinary assumptions of cost-based rational decision-making begin to break down?
  • Hybrid modelling approaches which combine GIS-based cost analyses with agent-based, cellular automata or other simulation approaches for modelling diffusion, colonization and dispersal.
  • Time-cost studies, that seek to understand and incorporate the role of travel time in movement-based studies. Which agents could arrive at which times, and how does this affect our interpretation of past population dynamics?
  • Studies that specifically address the question of scale. Can the same methods and techniques applied to global studies of population dispersal also be applied to micro-scale studies of movement around site habitation areas? If not, why not?
  • Critical examinations of particular concepts, approaches, or methods.
  • Artificial Intelligence in the archaeology of movement. Despite breathless enthusiasm in every discipline, one of the greatest limitations of AI, its lack of explanatory power, seems to pose an enormous challenge to archaeological applications, where exact pattern replication would seem to be secondary to understanding how and why such patterns emerge.
  • New directions extending the theoretical reach of cost and diffusion pathways beyond just movement across the physical landscape, into theoretical domain of innovation diffusion (Hägerstrand 1967)
  • Any other approach to the analysis of past populations movement in time and space that would seem to be relevant to the integrative objectives of the session.

References

Ammerman, A. J., & Cavalli-Sforza, L. L. (1979). The wave of advance model for the spread of agriculture in Europe. In Transformations (pp. 275-293). Academic Press.

Bilotti, G., Kempf, M., & Morillo Leon, J. M. (2024). Modelling land and water based movement corridors in the Western Mediterranean: a least cost path analysis from chalcolithic and early bronze age ivory records. Archaeological and Anthropological Sciences, 16(8), 1-25.

Gravel-Miguel, C., & Wren, C. D. (2018). Agent-based least-cost path analysis and the diffusion of Cantabrian Lower Magdalenian engraved scapulae. Journal of Archaeological Science, 99, 1-9.

Güimil-Fariña, A., & Parcero-Oubiña, C. (2015). “Dotting the joins”: a non-reconstructive use of Least Cost Paths to approach ancient roads. The case of the Roman roads in the NW Iberian Peninsula. Journal of Archaeological Science, 54, 31-44.

Hägerstrand, T. (1967) [1953]: Innovation diffusion as a spatial process. Chicago: University of Chicago Press.

Howey, M. C. (2007). Using multi-criteria cost surface analysis to explore past regional landscapes: a case study of ritual activity and social interaction in Michigan, AD 1200–1600. Journal of Archaeological Science, 34(11), 1830-1846.

Seifried, R. M., & Gardner, C. A. (2019). Reconstructing historical journeys with least-cost analysis: Colonel William Leake in the Mani Peninsula, Greece. Journal of Archaeological Science: Reports, 24, 391-411.

Verhagen, P., Nuninger, L., & Groenhuijzen, M. R. (2019). Modelling of pathways and movement networks in archaeology: an overview of current approaches. Finding the limits of the limes: Modelling demography, economy and transport on the edge of the Roman empire, 217-249.

Vita-Finzi, C., Higgs, E. S., Sturdy, D., Harriss, J., Legge, A. J., & Tippett, H. (1970, December). Prehistoric economy in the Mount Carmel area of Palestine: site catchment analysis. In Proceedings of the prehistoric society (Vol. 36, pp. 1-37). Cambridge University Press.

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S36: To Inform and Inspire: The Reuse of Archaeological and Heritage Data in Support of Nature Based Responses to Climate Change and Biodiversity Loss.

Session Organisers:
Claire Boardman, University of York
Nicki Whitehouse, University of Glasgow
Marian Berihuete-Azorin, Universitat Autònoma de Barcelona

Description

Session Format: Standard

Adaption and mitigation strategies for protecting the global historic environment are now being discussed and planned within the institutions, organisations and others entrusted with its care. However, as Fluck & Guest (2022) assert, “… our knowledge and skills as archaeologists are also relevant to supporting society in adapting to a changing climate and a low carbon future”. Indeed, recent years have seen an increase in academic and practice-based initiatives that use archaeology and heritage data to support the planning and implementation of nature-based responses, such as ‘rewilding’, to climate change and biodiversity loss.

The diverse and innovative work in this rapidly growing applied field of archaeology and heritage has already demonstrated its potential. Through the reconstruction of terrestrial paleoenvironments and ecologies (Whitehouse et al., 2023) or the restoration of biodiversity in marine and estuarine ecosystems (Morel et al., 2021) and the modelling of their change over time, possible and probable future options have been both challenged and expanded. Additionally, archaeobotanical data has been reused to support species reintroduction, increasing biodiversity and creating the potential for new sustainable commercial opportunities within local circular economies (Berihuete-Azorin et al., 2024).

Further, the analysis of traditional language(s) place names has recovered knowledge such as the location and nature of areas of lost woodland in Scotland (Natural Scotland, 2024). While the integration of traditional and Indigenous concepts of land relationships, resilience and resistance (Berkes et al; 1994; Emperaire, 2000; Chiblow, & Meighan, 2024; McDermott & Craith, 2024) with scientific understanding has been used to engage and inspire the collective imaginations of modern populations.

This work is enabled by an array of established and emerging digital geoarchaeology methods and technologies (Siart et al., 2017) underpinned by advancements in the creation and interoperability of large-scale, complex archaeological datasets (Lewis & Whitehouse, 2020) and the integration of archaeological data with non-archaeological data such as the multi- and hyperspectral imaging data generated by precision agriculture activities (Optiz et al., 2023). For example, GIS modelling of geophysical and geoarchaeological was used to define the Rungholt medieval dyke system of North Frisia and sequence coastal inundation events (Wilken et al., 2022), while agent-based modelling was used to analyse the formation of and biodiversity change within the deep chronologies of sediment traps in Engaruka, Tanzania (Kabora et al., 2020). Further, annotated historical maps and satellite and LIDAR imagery are being used to build AI/ML tools to automatically identify archaeological sites and features ahead of landscape rewilding (www.archai.io).

This session aims to share recent and current studies, syntheses or practices dealing with the reuse of archaeological or heritage data – in any or multiple formats – in support of climate change adaption, mitigation and/or biodiversity recovery. At the same time, consideration will be given to common themes and the extent to which current knowledge, skills, datasets, technologies and networks support these. Topics that might be addressed include but are not limited to the:

  • Development of new data models, methodologies or products
  • Reconstruction and application of place-based paleoenvironments and ecologies
  • Extraction of environmental or ecological data from image or sound collections
  • Leverage of intangible heritage to recover lost practices and knowledges
  • Inspiration for new or renewed local products, services and economies
  • Exploration of collaboration models with other expert communities of practice
  • Transformational public engagement leading to behaviour change

References

Berihuete-Azorin, M. et al. (2024) ‘Archaeobotany in an era of change and challenge: potential and fragility of macro- and micro-remains’, World archaeology. Informa UK Limited, pp. 1–16. doi: 10.1080/00438243.2024.2382140.

Berkes, F., C. Folke, and M. Gadgil. 1994. “Traditional Ecological Knowledge, Biodiversity, Resilience and Sustainability.” In Biodiversity Conservation: Problems and Policies. Papers from the Biodiversity Programme Beijer International Institute of Ecological Economics Royal Swedish Academy of Sciences, edited by C. A. Perrings, K.-G. Mäler, C. Folke, C. S. Holling, and B.-O. Jansson, 269–287. Dordrecht: Springer Netherlands.

Chiblow, S. and Meighan, P. J. (2024) ‘Anishinaabek Giikendaaswin and Dùthchas nan Gàidheal: concepts to (re)center place-based knowledges, governance, and land in times of crisis’, Ethnicities. SAGE Publications, 24(4), pp. 617–634. doi: 10.1177/14687968231219022.

Emperaire, L. 2000. “La biodiversité Agricole en Amazonie Brésilienne: Ressource et Patrimoine.” Journal d’Agriculture Traditionnelle et de Botanique Appliquée 42 (1): 113–126. https://doi.org/10.3406/jatba.2000.3732

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S37: Computational and Landscape Archaeology in the renovation of surface survey methodologies

Session Organisers:
Arnau Garcia-Molsosa, Catalan Institute of Classical Archaeology (ICAC)
Iban Berganzo-Besga, University of Toronto Mississauga
Hector A. Orengo, Catalan Institution for Research and Advanced Studies (ICREA) & Barcelona Supercomputing Center
Nazarij Buławka, Catalan Institute of Classical Archaeology; University of Warsaw

Description

Session Format: Standard

Remains of artefacts, architecture and other features visible on the earth surface are one of the main instruments for archaeologists to understand how past human populations inhabited and transformed the environment. Beyond the more traditional objective of localizing the best sites to excavate, surface record can be exploited by itself for the analysis of past cultural phenomena at both local and/or regional levels.

In the study of this complex surface record, the development of geospatial conceptual frameworks, methods and technologies played a central role in how archaeologists record field data and analyse the resulting datasets (Wheatley and Gillings 2013). One outstanding example of this integration can be traced since the introduction of the concept of systematic pedestrian survey at regional-scale, with the measuring of pottery scatters as its main target. This approach has a strong development in Eastern Mediterranean (Knodell et al. 2023), and in Greece in particular, since the 1950s, with multiple projects active nowadays, some of them with a long tradition (Bintliff et al. 1999; Alock and Cherry 2004). Its historical development has been parallel an intertwined with the development of geospatial technologies, and GIS in particular.

At the same time, the use of aerial and then satellite imagery changed the way surveys were done. First, the application of aerial and satellite imagery along with geophysics allowed the mapping of the structures visible at the sites (Campana and Piro 2009). Secondly, conducting remote sensing research allowed the mapping of countless sites for field verification (Casana 2014; Banning 2002, 136). In recent years, there has been an accumulation of developments on geospatial technologies that are being tested in the context of archaeological survey workflows, followed by a process of integration in the common practices of survey teams.

The availability of geospatial data has been exponentially increasing: multi-temporal sequences of aerial imagery, high-resolution orthomaps, multi-spectral and radar datasets, and digitised collection of archival photographic and cartographic datasets, are just some examples. This have been accompanied with the creation of specific platforms and software that allow the processing of this enormous geospatial information. The increasing extended use of Machine-Learning based approaches in archaeology is having a strong impact, which can be tracked in recent CAA and other international meetings. Some researches have use ML and DL algorithms to assist in the mapping of features such artificial mounds (Menze & Ur 2012; Berganzo-Besga et al. 2021 & 2023; Garcia-Molsosa et al. 2021) or hydraulic infrastructure (Bulawka et al. 2024 a&b).

The appearance of unmanned aerial vehicles (drones) has increased the resolution of captured imagery (Campana 2017), and given the archaeologists the capacity of capture information at the scale of specific archaeological features in large areas, something that was very costly until now, which limited works of Remote Sensing only to the study of large features that could be visible in large-scale images. Until recently, for example, it was not possible to use remote sensing to focus on the artifacts themselves. Thanks to the application of machine / deep learning with remote sensing, an opportunity for large-scale mapping pottery appeared (Orengo et al. 2021).

As this scale gap closes, the integration of multiple datasets, scales, techniques and sources in survey workflows, puts archaeological survey in front of a potential new step. In this session, we are inviting researchers interested in sharing how they are incorporating this new geospatial technologies to their surface surveys, and to discuss the current state of the art, and future perspectives for the application of computational methods in archaeological surveys.

At this session we would like to welcome every research on computational archaeology applied to field survey and the interpretation of surface datasets, in particular:

  • Theoretical and conceptual approaches to archaeological surface record.
  • Remote and on-field recording practices and the creation of archaeological geodatabases.
  • Automatised mapping of archaeological features, including artefacts, structures and landforms.
  • Statistics, computing modelling and other analytical methods applied to survey datasets.
  • Geophysics integration on archaeological surveys.
  • Design and development of regional surveys.

References

Alcock, S. E., and Cherry, J. F. (2004). Introduction. In Alcock, S. E., and Cherry, J. F. (eds.), Side-by Side Survey: Comparative Regional Studies in the Mediterranean World, Oxbow, Oxford, pp. 1–9.

Banning, Edward B. 2002. Archaeological Survey. New York: Kluwer Academic Press.

Bintliff, John L., Phil Howard, and Anthony Snodgrass. 1999. ‘The Hidden Landscape of Prehistoric Greece’. Journal of Mediterranean Archaeology 12 (2): 139–68.

Buławka, N.; Orengo, H.A. 2024a. Application of Multi-Temporal and Multisource Satellite Imagery in the Study of Irrigated Landscapes in Arid Climates. Remote Sens. 16, 1997.

Buławka, N.; Orengo, H. A.; Berganzo-Besga, I. 2024 Deep learning-based detection of qanat underground water distribution systems using HEXAGON spy satellite imagery, Journal of Archaeological Science, Volume 171, 106053, https://doi.org/10.1016/j.jas.2024.106053

Berganzo-Besga, I., Orengo, H. A., Lumbreras, F., Carrero-Pazos, M., Fonte, J., & Vilas-Estévez, B. (2021). Hybrid MSRM-Based Deep Learning and Multitemporal Sentinel 2-Based Machine Learning Algorithm Detects Near 10k Archaeological Tumuli in North-Western Iberia. Remote Sensing (20), Article 20. https://doi.org/10.3390/rs13204181

Berganzo-Besga, I., Orengo, H. A., Lumbreras, F., Alam, A., Campbell, R., Gerrits, P. J., de Souza, J. G., Khan, A., Suárez-Moreno, M., Tomaney, J., Roberts, R. C., & Petrie, C. A. (2023). Curriculum learning-based strategy for low-density archaeological mound detection from historical maps in India and Pakistan. Scientific Reports 13 (1), Article 1. https://doi.org/10.1038/s41598-023-38190-x

Campana, Stefano. 2017. ‘Drones in Archaeology. State-of-the-Art and Future Perspectives’. Archaeological Prospection 24 (4). https://doi.org/10.1002/arp.1569.

Campana, Stefano, and Salvatore Piro. 2009. Seeing the Unseen: Geophysics and Landscape Archeology. Boca Raton, London, New York, Leiden: CRC Press of Taylor & Francis Group. https://doi.org/10.1002/arp.365

Casana, Jesse. 2014. ‘Regional-Scale Archaeological Remote Sensing in the Age of Big Data’. Advances in Archaeological Practice 2 (03): 222–33. https://doi.org/10.7183/2326-3768.2.3.222

Garcia-Molsosa, A., Orengo, H. A., Lawrence, D., Philip, G., Hopper, K., & Petrie, C. A. (2021). Potential of deep learning segmentation for the extraction of archaeological features from historical map series. Archaeological Prospection 28 (2), 187–199. https://doi.org/10.1002/arp.1807

Knodell, Alex R., Toby C. Wilkinson, Thomas P. Leppard, and Hector A. Orengo. 2023. ‘Survey Archaeology in the Mediterranean World: Regional Traditions and Contributions to Long-Term History’. Journal of Archaeological Research 31 (2): 263–329. https://doi.org/10.1007/s10814-022-09175-7h

Menze, B. H., & Ur, J. A. (2012). Mapping patterns of long-term settlement in Northern Mesopotamia at a large scale. Proceedings of the National Academy of Sciences 109(14), E778–E787. https://doi.org/10.1073/pnas.1115472109

Orengo, H. A., Conesa, F. C., Garcia-Molsosa, A., Lobo, A., Green, A. S., Madella, M., & Petrie, C. A. (2020). Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data. Proceedings of the National Academy of Sciences 117( 31), 18240–18250. https://doi.org/10.1073/pnas.2005583117

Orengo, Hector A., Arnau Garcia-Molsosa, Iban Berganzo-Besga, Juergen Landauer, Paloma Aliende, and Sergi Tres-Martínez. 2021. ‘New Developments in Drone-Based Automated Surface Survey: Towards a Functional and Effective Survey System’. Archaeological Prospection, no. November 2020, 1–8. https://doi.org/10.1002/arp.1822.

Wheatley, D., & Gillings, M. (2013). Spatial Technology and Archaeology: The Archaeological Applications of GIS. CRC Press.

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S38: Concepts, methods and techniques for online dissemination and querying of scientific 3D Cultural Heritage resources

Session Organisers:
Diego Jiménez-Badillo, National Institute of Anthropology and History (INAH)
Vera Moitinho de Almeida, University of Porto

Description

Session Format: Standard

As galleries, libraries, archives and museums (GLAM) embark on massive digitization projects, granting access to texts, images, sound recordings, and particularly 3D models, has become a major challenge. This is especially true in the case of multimedia data produced for research, which aims at improving the education of students and facilitating the discovery of new knowledge for the benefit of scholars (Frischer 2008). One important goal is achieving maximum dissemination under the FAIR (i.e., making data findable, accessible, interoperable, and reusable; Wilkinson et al. 2016) and CARE (i.e., collective benefit, authority to control, responsibility, ethics; Carroll et al. 2020) principles.

We invite researchers from any scientific field to join a discussion on the state-of-the-art in multimedia research-data dissemination, particularly cultural heritage 3D models. General topics for the session include (but are not limited to):

  • Conceptual and epistemological issues
  • Data dissemination workflows
  • Building online archives and repositories
  • Infrastructures
  • Digital data lifecycle
  • Data authentication and quality control
  • Digital rights management
  • Effective metadata structures
  • Preservation of digital data
  • Practical projects and case studies

The motivation for the session is to gain insight into the methods, procedures, and technologies currently adopted to create cultural heritage data repositories. Examples of the specific topics that may addressed are:

  1. How much the Semantic Web and Linked Data technologies – supported by ontological models such as CIDOC-CRM – have allowed disseminating textual, image and 3D data online, and how much have they fulfilled the promise of making data interactive, integrated, and contextualized, while facilitating Web persistence, machine readability, content repurposing (Isaksen, 2011:10). Moreover, how much have they facilitated content customization according to user profiles and preferences? (Bikakis et al., 2021).
  2. What are the best techniques and algorithms of Computer vision, Machine Learning and/or Artificial Intelligence to build search-engines for 3D models? (Jain & Mishra 2014; Lara López et al 2017; Rostami et al., 2019; Tangelder & Veltkamp 2008; Xie et al. 2017).
  3. What can we learn from the development of past and existing search engines of 3D models in terms of research objectives, strategies for student and scholar engagement, classes of data, among others? (Addis et al. 2003, 2005; Clark et al. 2002; Ekengren et al. 2019; Rowe et al. 2001; Rowe and Razdan 2002; Schurmans et al. 2002).
  4. How much a 3D search engine should rely on textual queries, and how much on shape-based searches? As discussed by Jiménez-Badillo et al. (2024) in a recent paper, one problem with the dissemination of 3D models online is that some systems grant access to 3D models based only on text queries. However, this strategy fails when keywords describing an object are unknown during the cataloguing process, or when important keywords for searching objects are unknown to the final users of the system. Thus, a pending challenge is how to build a system that analyses the visual characteristics of objects to recognise their shapes without relying exclusively on keywords.
  5. Finally, another important topic – raised by Koller et al. (2009:1) – is how to build “…open repositories of scientifically authenticated 3D models based on the example of traditional scholarly journals, with standard mechanisms for preservation, peer review, publication, updating, and dissemination of the 3D models”. Furthermore, how to face challenges, such as “…digital rights management for the 3D models, clear depiction of uncertainty in 3D reconstructions, version control for 3D models, effective metadata structures, long-term preservation, interoperability, and 3D searching”. Looking at the current bibliography, it is unclear how much these issues have been resolved or which solutions have become standard practice.

References

Addis, M., Boniface, M., Goodall, S., et al. (2003). SCULPTEUR: Towards a New Paradigm for Multimedia Museum Information Handling. In D. Fensel, K. Sycara, J. Mylopoulos (Eds.), The Semantic Web – ISWC 2003; Lecture Notes in Computer Science 2870 (pp. 582-596). https://doi.org/10.1007/978-3-540-39718-2_37

Addis, M., Martinez, K., Lewis, P., et al. (2005). New ways to search, navigate and use multimedia museum collections over the Web. In J. Trant, D. Bearman (Eds.), Museums and the Web 2005: Proceedings. Toronto: Archives & Museum Informatics. http://www.archimuse.com/mw2005/papers/addis/addis.html

Bikakis, A., Hyvönen, E., Jean, S., et al. (2021). Editorial: Special issue on Semantic Web for Cultural Heritage. Semantic Web 12(2): 163-167. https://doi.org/10.3233/SW-210425

Carroll, S. R., Garba, I., Figueroa-Rodríguez, O., et al. (2020). The CARE Principles for Indigenous Data Governance. Data Science Journal 19: 1-12. https://doi.org/10.5334/dsj-2020-042

Clark, J. T., Slator, B. M., Bergstrom, A., et al. (2002). DANA (Digital Archive Network for Anthropology): A model for digital archiving. In Proceedings of the 2002 ACM Symposium on Applied Computing (SAC ’02) (pp. 483-487). https://doi.org/10.1145/508791.508881

Ekengren, F., Callieri, M., Dininno, D., et al. (2021). Dynamic collections: A 3D web infrastructure for artifact engagement. Open Archaeology 7(1): 337-352. https://doi.org/10.1515/opar-2020-0139

Frischer, B. (2008). Introduction: From digital illustration to digital heuristics. In B. Frischer, A. Dakouri-Hild (Eds.), Beyond Illustration: 2D and 3D Digital Technologies as Tools for Discovery in Archaeology. Oxford: BAR Publishing, Bar International Series 1805, pp. 5-24.

Isaksen, L. (2011). Archaeology and the Semantic Web. Doctoral Thesis, University of Southampton. Faculty of Physical and Applied Sciences. School of Electronics and Computer Science. Pp. 259. http://eprints.soton.ac.uk/id/eprint/206421

Jain, S., Mishra, S. (2014). Survey paper on various 3D view based retrieval methods. International Journal of Engineering Research & Technology 3(2): 470-473.

Jiménez-Badillo, D., Mendoza-Montoya, O., Ruiz-Correa, S. (2024). Application of computer vision techniques for 3D matching and retrieval of archaeological objects. F1000 Research – New Digital Archaeologies 12: 182. https://doi.org/10.12688/f1000research.127095.2

Koller, D., Frischer, B., Humphreys, G. (2009). Research challenges for digital archives of 3D cultural heritage models. Journal on Computing and Cultural Heritage 2(3): article 7, pp. 1-17. https://doi.org/10.1145/1658346.1658347

Lara López, G., Peña Pérez Negrón, A., de Antonio Jiménez, A., et al. (2017). Comparative analysis of shape descriptors for 3D objects. Multimedia Tools and Applications 76: 6993-7040. https://doi.org/10.1007/s11042-016-3330-5

Rowe, J., Razdan, A. (2002). Digital library system. In Proceedings of the 2nd ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL’02) (pp. 382). https://doi.org/10.1145/544220.544329

Rowe, J., Razdan, A., Collins, D., et al. (2001). A 3D digital library system: Capture, analysis, query, and display. In Proceedings of the 4th International Conference on Digital Libraries (ICADL) (pp. 1-9).

Rostami, R., Bashiri, F. S., Rostami, B., et al. (2019). A survey on data-driven 3D shape descriptors. Computer Graphics Forum 38(1): 356-393. https://doi.org/10.1111/cgf.13536

Tangelder, J. W. H., Veltkamp, R. C. (2008). A survey of content based 3D shape retrieval methods. Multimedia Tools and Applications 39: 441-471. https://doi.org/10.1007/s11042-007-0181-0

Schurmans, U., Razdan, A., Simon, A., et al. (2002). Advances in geometric modeling and feature extraction on pots, rocks and bones for representation and query via the Internet. In G. Burenhult, J. Arvidsson (Eds.), Archaeological Informatics: Pushing the Envelope. Proceedings of the 29th Conference on Computer Applications and Quantitative Methods in Archaeology (CAA2001), Gotland. Oxford: Archaeopress, BAR International Series 1016, pp. 191-202.

Wilkinson, M., Dumontier, M., Aalbersberg, I., et al. (2016). The FAIR Guiding principles for scientific data management and stewardship. Scientific Data 3. https://doi.org/10.1038/sdata.2016.18

Xie, J., Dai, G., Zhu, F., et al. (2017). DeepShape: Deep-learned shape descriptor for 3D shape retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence 39(7): 1335-1345. https://doi.org/10.1109/TPAMI.2016.2596722

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S39: From FAIR principles to FAIR practices in Archaeological Remote Sensing (including archaeo-geophysics) – Are we there yet?

Session Organisers:
Agnes Schneider, Leiden University
Alessia Brucato, University of Bari Aldo Moro (UNIBA) – Institute of Heritage Science National Research Council of Italy (ISPC CNR)
Maria-Elena Castiello, University of Lausanne
Giuseppe Guarino, Alma Mater Studiorum University of Bologna (UNIBO)

Description

Session Format: Standard

Large-scale data collection is an established practice in Archaeological Remote Sensing. Air- and space-borne sensors deliver an ever-growing proportion of data sets, and in the last decade geophysical prospection has started to collect data on a large scale as well. Evaluating the increasing amount and variety of sources requires analytical methods to handle this data deluge, namely (semi-) automated analysis methods. With regard to air- and space-borne imagery, well-developed workflows and established approaches to process and analyse the most common datasets (panchromatic [1], RGB, multi- [2], and hyperspectral [3], LiDAR [4, 5], SAR[6] and UAV [7] imagery) for archaeological and palaeoenvironmental investigation as well as heritage preservation are already available. At the same time, geophysical prospection still involves many specific approaches and an open and exciting discussion about the standardisation of data analysis and automatic methods [8, 9], given their different specificities (GPR – ground penetrating radar, Magnetometry, ER – earth resistance, EM – electromagnetic conductivity [10, 11] and seismic). A few strategies are: [12-14]. The nearly two decades in which semi-automated methods have been applied to large-scale archaeological remote sensing data show a constant development of methods (loosely relying on developments in Remote Sensing and Computer Science). A wide variety of solutions have been developed for different questions with recurring patterns. FAIR principles [15] were introduced in 2014, and recently research data management has also become more and more of a central focus in scientific work. Still, there is a lack of broadly used research standards on local, regional, national, international, and interdisciplinary scales, which leads to the lack of transparency, transferability and best practices [16, 17]. With initiatives on different levels, this landscape is starting to change and evolve. Together, we have to create common community standards and best practices that lead to FAIR and Open Data. On top of that, reproducible research practices and addressing sustainability issues have to be discussed and implemented. Nonetheless, there is currently a general lack of an agenda for FAIR practices, best practices and open, reproducible workflows. There is therefore a long way to go [18], but this is about to change [19]. Interdisciplinary collaborations through networks and governmental portals can help in elevating data practices, to maximise the potential of data reuse in order to achieve responsible stewardship and impactful discoveries. Our session aims to bring together experts and colleagues interested in open science [20], and the implementation of the FAIR principles as FAIR practices in Archaeological Remote Sensing (including archaeo-geophysics) to exchange about the following topics : 

  • What do “working reproducibly” and “FAIR practices” mean for you? Which steps are there to take?
  • What barriers and problems do you see from your experience?
  • How does your institution/lab/working group address reproducibility and replicability?
  • Which community standards have you transformed into FAIR best practices?
  • How are you coupling FAIR practices with AI methods?
  • How is metadata of the capturing and processing method FAIRly provided?

We encourage (also early career) researchers and colleagues to present case studies and ongoing investigations highlighting these topics and approaches.

References

[1] Bulawka & Orengo (2024) DOI: 10.1016/j.jas.2024.106053

[2] Abate et al. (2020) DOI:10.3390/rs12081309

[3] Guyot thesis Guyot (2021) https://theses.fr/2021REN20054

[4] EAC Guidelines 10 forthcoming

[5] Fiorucci et al. 2022 DOI:10.3390/rs14071694

[6] Cigna, et al. (2023). DOI: 10.1080/10095020.2023.2223603

[7] Orengo et al. (2020) DOI: 10.1002/arp.1822

[8] Verdonck et al. (2019). DOI: 10.1016/B978-0-12-812429-1.00006-4

[9] Opitz & Herrmann (2021). DOI: 10.5334/jcaa.11

[10] EAC Guidelines 2 (2015). DOI: 10.5281/zenodo.10671299

[11] Martorana et al. (2023). DOI: 10.3390/heritage6030154

[12] Hegyi et al. (2019) DOI: 10.1002/arp.1752

[13] Kücükdemirci & Sarris (2020). DOI: 10.1002/arp.1763

[14] Kuna et al. (2021) DOI: 10.1016/j.jas.2020.105298

[15] Wilkinson et al. (2016). DOI: 10.1038/sdata.2016.18

[16] Barton et al. (2022) DOI: 10.1073/pnas.2202112119

[17] Janz and Freese (2020) DOI:10.1017/S1049096520000943

[18] Nicholson et al. (2023) DOI: 10.1017/aap.2022.40

[19] Schöch (2023) DOI:10.1007/s42803-023-00073-y

[20] Marwick et al. (2017) DOI:10.17605/OSF.IO/3D6XX

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S40: MuVAMoLa – Multivariate Approaches to Mortuary Landscapes

Session Organisers:
Tucker Deady, University of Toronto
Timo Geitlinger, University of Zurich

Description

Session Format: Standard

Mortuary scholarship has perhaps one of the longest histories in archaeological research, but it is a history riddled with bias based on visibility, durability, and public interest. Often most evident in regions where burial practices were accompanied by the erection of monumental architecture, the inclusion of sensational objects, or carry imaginary cultural significance, mortuary contexts have drawn in significant amounts of research. Early scientific endeavors yielded abundant contextual data on burial monuments, ritual behavior, and interred objects. Due to the quality of documentation, however, through locational, temporal, and financial predispositions, legacy datasets tend to be heterogenous and noisy and have large gaps in the types of information collected and recorded (see Cooper et al. 2022). Quantitative analyses of mortuary practices are thus commonly met with specific data-related challenges that have proven themselves obstacles in methodological proceedings. How do we therefore reconcile with this biased history of research while still utilizing the documented material and moving forward into more collaborative conversations within both computational and theoretical scholarship? Mortuary behavior is inherently linked to individual and group identity and should be seen as both agents creating cultural and social connections and manifestations of these relations. Simultaneously, burial construction and material inclusions are highly selective and cannot be taken to represent a daily reality of the associated people (Porter 2016). As archaeologists, we must ask how we can use the information we gather from burials, intentionally closed contexts, and speak about the living people and the materialization of their self-perception. Likewise, the placement of tombs within specific environments reveals complexities of cultural expressions that permeate past landscapes. The spatial significance of mortuary evidence in association with material culture, when placed under the scrutiny of quantitative analyses, can further enhance the theoretical and methodological approaches to archaeological landscapes as a whole. While early pioneers of computational archaeology conducted quantitative analyses to study burial contexts within individual sites (Hodson 1968), more recent studies use network analysis (Bourgeois and Kroon 2017; Sosna 2023), and principal components and correspondence analyses (Kjeld Jensen and Høilund Nielson 1997; Kassabaum 2011), amongst other multivariate methods (Nakoinz 2013), to study large scale landscape connections of mortuary contexts. The aim of this session is to bring together scholars from diverse backgrounds who study burials through multivariate quantitative approaches who are interested in discussing qualitative implications, best (and worst) practices, and potential caveats for future scholarship. We invite authors who:

  • Apply multivariate methods to burials and their landscapes
  • Work on multivariate methods that are applicable to burial practices
  • Develop methodological or theoretical frameworks for the successful application of multivariate and/or spatial methods to study burial contexts.

References

Bourgeois, Quentin. and Erik Kroon. 2017. “The Impact of Male Burials on the Construction of Corded Ware Identity: Reconstructing Networks of Information in the 3rd Millennium BC.” PLoS One (10): e0185971–e0185971. https://doi.org/10.1371/journal.pone.0185971

Cooper, Anwen, Duncan Garrow, Catriona Gibson, Melanie Giles, and Neil Wilkin. 2022. Grave Goods: Objects and Death in Later Prehistoric Britain. Oxford ; Oxbow Books. https://doi.org/10.5284/1052206

Ekengren, Fredrik. 2013. “Contextualizing Grave Goods: Theoretical Perspectives and Methodological Implications.” In The Oxford Handbook of the Archaeology of Death and Burial. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199569069.013.0010.

Gosden, Chris, Tyler Franconi, Letty ten Harkel. 2021. “Introduction.” In English Landscape and Identities. Investigating Landscape Change from 1500 BC to AD 1086, edited by Anwen Cooper, Miranda Creswell, Victoria Donnelly, Tyler Franconi, Roger Glyde, Chris Gosden, Chris Green, Zena Kamash, Sarah Mallet, Laura Morley, Daniel Stansbie, and Letty ten Harkel. Oxford: Oxford University Press. https://doi.org/10.1093/oso/9780198870623.001.0001

Hodson, Frank Roy. 1968. The La Tène Cemetery at Münsingen-Rain, Catalogue and relative Chronolog. Acta Bernensia V, Bern: Verlag Stämpfli & Cie AG.

Kassabaum, Megan. (2011). “Looking Beyond the Obvious: Identifying Patterns in Coles Creek Mortuary Data.” Southeastern Archaeology 30 (2): 215-225. https://doi.org/10.1179/sea.2011.30.2.002

Nakoinz, Oliver. 2013. Archäologische Kulturgeographie der ältereisenzeitlichen Zentralorte Südwestdeutschlands. “Universitätforschungen zur prähistorischen Archäologie” 224, Bonn: Verlag Dr. Rudolf Habelt GmbH.

Porter, Anne. 2016. “The Materiality of Mourning.” In How to Cope with Death: Mourning and Funerary Practices in the Ancient Near East. Proceedings of the International Workshop held at the University of Firenze, December 5-6, 2013, edited by C Felli. Pisa. 157-188

Sosna, Daniel. 2023. “Mortuary Archaeology Networks.” In The Oxford Handbook of Archaeological Network Research, edited by Tom Brughmans, Barbara J. Mills, Jessica Munson, and Matthew A. Peeples. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780198854265.013.25

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S41: Archaeological Network Research

Session Organisers:
Tom Brughmans, Aarhus University
Paula Gheorghiade, University of Helsinki

Description

Session Format: Standard

Archaeological network research is the study of past relational phenomena using network methods and theories. These phenomena could concern the distribution of material culture through artefact co-occurrence, past maritime and pedestrian mobility, visual signaling and visual prominence, food webs, knowledge creation, illicit trade in antiquities and much more. Computational network methods are invaluable in archaeological network research, as they enable the formal representation and analysis of network data and its analysis, and to test relational theories. There is huge potential in further developing archaeological network research to address topics for which both material culture and network methods are not merely desirable but required. Recent overviews of the field (Brughmans and Peeples 2023, 271-280; Munson et al. 2023) have revealed the following research lines to be particularly promising:

  • Empirical past social network reconstruction
  • Socioecological networks and environmental variability
  • Cultural evolution and biological networks
  • Past economies
  • Textual and material networks
  • Networks of archaeological practice

This session aims to actively contribute to the future development of archaeological network research. It particularly welcomes papers addressing original method and theory work along the above lines, as well as innovative applied case studies in those research lines. It additionally provides a suitable venue to present and debate any archaeological network studies regardless of material, period, method or theory.

References

Brughmans, T., & Peeples, M. A. (2023). Network Science in Archaeology. Cambridge Manuals in Archaeology. Cambridge: Cambridge University Press.

Munson, J., Mills, B. J., Brughmans, T., & Peeples, M. A. (2023). Anticipating the Next Wave of Archaeological Network Research. In T. Brughmans, B. J. Mills, J. Munson, & M. A. Peeples (Eds.), The Oxford Handbook of Archaeological Network Research (1st ed., pp. 664–674). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780198854265.013.44

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S42: From Code to Discovery: Deep Learning in Archaeological Research

Session Organisers:
Nevio Dubbini, Miningful srls
Ivan Tyukin, King’s College London
Elisa Paperini, University of Pisa
Quirino Saraceni, University of Pisa

Description

Session Format: Standard

The integration of Artificial Intelligence (AI), particularly Neural Networks (NNs) using Deep Learning methodologies, into archaeological research marks a significant shift in how cultural heritage is studied and interpreted. Archaeology deals with complex and multifaceted data, ranging from satellite and geospatial data to artefact analysis and ancient texts interpretation. NNs provide powerful means to streamline and enhance tasks that require time, prior knowledge and expertise, such as, but not limited to, classifying artefacts and determining their chronology, recognising archaeological sites from LiDAR and other geospatial data, analysing settlement patterns, processing and interpreting ancient texts. Behind the development and growth of NNs is Python, one of the most adopted languages for AI implementation, which empowers well-known frameworks such as TensorFlow, PyTorch, and Keras. On the other side, web-based tools are lowering the barrier to entry, allowing neural network development even without advanced coding knowledge. The aim of this session is to foster a collaborative network dedicated to exploring the applications of Artificial Intelligence in Archaeology, specifically related to NNs, encouraging the open sharing of programming skills, methods, scripts, and tools to harness AI’s full potential in Archaeology. We welcome contributions from across the spectrum of every neural network type, each offering capabilities for addressing challenges within archaeological research, processing data obtained from images, satellite imagery, maps, time series, texts and content creation through generative AI. Submissions employing methodologies beyond Python, such as ANNs via web-based tools or other platforms, and discussions on the challenges and opportunities presented by data analysis and processing methods, are also welcomed. Participants will have the opportunity to:

  • Showcase the datasets used in their research, highlighting the role of data quality and diversity in model performance;
  • Present the code and frameworks behind their NNs creation and training, including any custom solutions;
  • Share the programming environments used for their projects;
  • Discuss the parameters and hyperparameters employed for Neural Networks training, and how these choices influence model outcomes;
  • Explore the algorithms driving their Neural Network and Deep Learning models, and their implications for solving specific archaeological problems.

References

Cobb, P. 2023, Large Language Models and Generative AI, Oh My!: Archaeology in the Time of ChatGPT, Midjourney, and Beyond in «Advances in Archaeological Practice», 11, 363-369.

Grove M., Blinkhorn J. Neural networks differentiate between Middle and Later Stone Age lithic assemblages in eastern Africa, in «PLoS ONE», 15(8), e0237528.

Gualandi M.L., Gattiglia G., Anichini F An Open System for Collection and Automatic Recognition of Pottery through Neural Network Algorithms, «Heritage», 4, 140-159.

Li G., Dong, J., Che, M., Wang, X., Fan, J., & Dong, G. (2024). GIS and machine learning models target dynamic settlement patterns and their driving mechanisms from the Neolithic to Bronze Age in the Northeastern Tibetan Plateau. Remote Sensing, 16 (8), 1454. https://doi.org/10.3390/rs16081454.

Navarro P., Cintas C., Lucena M., Fuertes J.M., Segura R., Delrieux C., González-José R. 2022, Reconstruction of Iberian ceramic potteries using generative adversarial networks, in «Scientific Reports», 12, 10644.

Ostertag C., Beurton-Aimar M. 2020, Matching ostraca fragments using a siamese neural network, in «Pattern Recognition Letters», 131, 336–340.

Verschoof-van der Vaart, W. B., & Lambers, K. 2022, Applying automated object detection in archaeological practice: A case study from the southern Netherlands, in «Archaeological Prospection», 29(1), 15–31.

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S43: Reproducibility in the age of AI and beyond: what is really important for reusable research?

Session Organisers:
Lutz Schubert, University of Cologne
Agnes Schneider, Leiden University

Description

Session Format: Standard

Reproducibility and replicability are essential for serious research, as otherwise results cannot be verified and thus are essentially worthless for future work and the results themselves may even be wrong. According to a survey by Nature 70% of publications from different scientific domains were not reproducible (Baker, 2016). Figures vary between studies and scientific areas, but they all lead up to the fact that a large number of published research results are unverifiable, as either attempts to reproduce them fail or not enough information is available to reproduce them in the first instance. Reproducibility (and replicability) face multiple issues – ranging from technical changes to lack of information in the publication. Some of these issues can therefore be directly blamed on the author(s) whereas others are due to natural developments, such as changes in code or in hardware. We therefore need to differentiate between the levels of involvement required by the author(s) and, in fact, the publishing house / library hosting the work. The questions in this context are, however, how much effort can seriously be expected, and which aspects are really important for reproducibility and replicability. As such, e.g., hardware and software, including the Operating System, are subject to constant changes and code that may run and compile perfectly on one day, may not execute properly on the next. In particular where the code used for creating the results depends on libraries or modules developed by someone else, any update or change may lead to problems and therefore to unverifiable results. This is an issue typically faced in sustainable archiving of research results and requires e.g. storing the whole computation environment of the researchers in the form of a virtual machine. Others have suggested that publishing houses not only need to review the quality of the paper but also try to reproduce the results to verify correctness prior to publication (e.g. Hutter, 2022) – which leads to high effort by large groups of experts and according costs. It also does not guarantee that the results can be replicated (as opposed to reproduced (Community, 2022)) and therefore be taken up by future researchers. In the age of AI and of an increased use of Neural Networks (LLM, GAN etc.) to generate research results, reproducibility faces completely new challenges. Even if the same results can be achieved through storing the controlling parameters, such as seed, temperature etc. (Reddy, 2024) [REF], this does not mean that the results are robust against changes. What is more, most AI are affected by the way that the query is posed, which additional documents are provided etc. and as the Neural Network is trained further, the results may vary even under the same seed and prompt conditions. Storing all contextual information in a virtual environment takes up an increasing amount of space and complexity (Mellor, 2022). This begs the question whether all information and all contexts always need to be stored. For example, a simple computation for calculating an average over all data collected does not necessitate that the whole MATLAB environment is stored with the publication – but instead, the data and the formula / algorithm used for calculation are essential. Similarly, a complex code is not useful if the underlying algorithm is not explained and the code is not documented. A simple “store everything in a Virtual Machine” is therefore neither sufficient for replicability, nor efficient. The questions therefore are which information is actually relevant for reproducing and replicating the results, how can it be maintained and made sustainable for a longer period of time, and who is responsible for this? How much effort is an author willing to make after 5, 10 or 20 years after the publication? This session focuses on all aspects related to reproducibility and sustainability of research results in archaeology with a specific focus on these three questions: What, How and Who? We invite papers on, but not limited to

  • Best methods of preserving research results in a reproducible fashion over long time
  • Methods to check for reproducibility and replicability
  • Means to reduce the for storing and maintaining reproducible results
  • Discussion on which aspects of research results are relevant for reproduction and which are not

REFERENCES

Baker, M., 2016. 1,500 scientists lift the lid on reproducibility. Nature 533, 452–454. https://doi.org/10.1038/533452a

Community, T.T.W., 2022. The Turing Way: A handbook for reproducible, ethical and collaborative research. https://doi.org/10.5281/ZENODO.3233853

Hutter, F., 2022. AutoML | Introducing Reproducibility Reviews. URL https://www.automl.org/introducing-reproducibility-reviews/ (accessed 9.12.24).

 Mellor, C., 2022. Tape (and DNA?) needed to meet archive demand by 2030. Blocks Files. URL https://blocksandfiles.com/2022/08/09/dataverse-storage_requirements/ (accessed 9.12.24).

Reddy, P., 2024. Controlling Creativity: How to Get Reproducible Outcomes from LLMs. Medium. URL https://medium.com/@prabhavithreddy/controlling-creativity-how-to-get-reproducible-outcomes-from-llms-016ec0991891 (accessed 9.12.24).

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S44: Digital and computational methods in the studies of rock art and ancient art: beyond tracing the past

Session Organisers:
Oliver Vogels, University of Cologne
Julian Jansen van Rensburg, Chronicle Heritage
Paolo Medici, Centro Camuno di Studi Preistorici di Valcamonica
Ashely Green, University of Gothenburg

Description

Session Format: Standard

This session aims to answer how rock art research and related fields, such as epigraphy and the study of wall paintings, have developed through digital methods. Living in a fast evolving technical world we want to ask: do research questions about space relations change through the use of digital methods such as GIS approaches or spatial statistics? What new insights about past cultures can be gained from statistical approaches, network analysis, or machine learning? Is AI about to help us crack the code of symbolic encryption and to better understand past worldviews? Furthermore we want to address whether new insights can be gained by combining legacy data with recent digital methods. Which new insights do multi-modal approaches bring in? And how can we publish and structure digital collections of rock art in a way that allows us to include its specific cultural and spatial characteristics and contexts?

In contrast to material culture, rock art, as well as other forms of artistic expression in ancient societies, tell us about the past from the perspective of the people themselves. Due to this, it can hardly be underestimated as both cultural heritage and a source of information about these past societies. On the other hand, rock art is widely understood as a communication system that is deeply rooted in the respective worldview of its authors. In other words, rock art is ‘symbolically encoded’ (Solomon 1997, Davidson 2018, Challis et al. 2013, Martel 2019). Use, function, meaning or context of rock art are therefore not directly accessible from cultures who do not share the same symbolic system. This problem was considered early on when archaeologists in the 1960s and 1970s failed to explain rock art – or the results of quantitative approaches – out of their own personal and cultural background (Lewis-Williams & Loubser 1986). Although the social and symbolic peculiarity of rock art was mostly articulated in southern Africa (Mitchell 2005) and Australia (Layton 2992) in the 1980s and 1990s, resting its interpretation solely on ethnographic observations and analogies soon made its way into rock art research world-wide (Solomon & Bahn 2023). While this scholarly process emphasized the social and ritual relevance of the production and consumption of rock art, other aspects such as its spatial or regional relationships or information about the societies to which it refers, such as gender, different social roles or the authors’ ecological knowledge etc, were often neglected. Consequently, and perhaps also driven by the increasing power of computational archaeology, Taçon and Chippindale demanded in 1998 to bring together (ethnographically) “informed” and “formal” methods:

For much rock art, beginning with the Paleolithic art of the deep European caves, we have no basis for informed knowledge. There we must work with formal methods, those that depend on no inside knowledge, but which work when one comes to the stuff ‘cold’, as a prehistorian does. The information available is then restricted to that which is imminent in the images themselves, or which we can discern from their relations to each other and to the landscape, or by relation to whatever archaeological context is available” (Taçon & Chippindale 1998: 7-8, original emphasis).

Since then, an interpretative turn took place in rock art studies towards seeking rather local, contextualized, situational explanatory approaches than big theories (Conkey 2018: 39, Van Dyke 2022). Epistemologically, this turn also questions whether processual and post-processual approaches are strictly contradictory or rather complementary. Bringing together informed and ‘formal methods’ (sensu Taçon and Chippindale 1998), however,  requires a certain way of recording which departs from selection of certain motifs towards more inclusive methods that aim to record all of what is (and once was) depicted. It is no surprise that with the technological progress in digital photogrammetric methods (digital photography, laser scanning, infrared, LIDAR, RTI, SFM) and the availability of representational methods (3D Models) research focused on digital recording methods (Bourdier et al. 2015, Díaz-Guardamino 2015, Jalandoni et al. 2018, Horn et al. 2018, Horn et al. 2019, Skoog et al. 2022, Carrero-Pazos et al. 2022). These technologies are still evolving with ever-improving methods that bring to light even those parts of the art vanished over time due to site formation and taphonomic processes. Further to this, digital methods are allowing for the high-resolution digital preservation and ethical dissemination of rock art.

The way rock art is recorded highly influences how it can be analyzed and which questions can be addressed. Perhaps due to the large variety of documentation methods, but foremost due to the uniqueness of each prehistoric culture’s worldview and symbolic encoding system, a formalized toolset hardly developed until today in this field of research. In this quality, the research of rock art differs from many of its neighboring archaeological disciplines, where remote sensing and GIS techniques, or statistical and quantitative methods have become permanent components of the toolset to reconstruct aspects of past cultures (Chase et al. 2017, Parcak 2009, Conolly & Lake 2006, McCall 2018, Carlson 2018). Of course, beyond digital recording techniques GIS methods such as viewshed analysis, geostatistics, virtual reconstruction or remote-sensing approaches were used to rediscover the way historical and prehistoric cultures conceptualized cognitive spaces and image programmes (Domingo & Gallinaro 2021, Tonazzini et al. 2019, Vogels et al. 2021, Wienhold & Robertson 2018).

This session seeks to answer how the research of rock art developed through digital methods. Where are we now 25 years after Chippindale and Taçon’s demand to widen the methodological scope towards the inclusion of both ethnographic sources and formal methods? Looking beyond digital documentation and presentation methods we believe it is time to take a look back into the future and to address how far our understanding of ancient cultures has developed.

References

Bourdier, C, Fuentes, O and Pinçon, G 2015 Contribution of 3D technologies to the analysis of form in Late Palaeolithic rock carvings: The case of the Roc-aux-Sorciers rock-shelter (Angles-sur-l’Anglin, France), Digital Applications in Archaeology and Cultural Heritage, 2(2): 140–154. DOI: https://doi.org/10.1016/j.daach.2015.05.001.

Carlson, D L 2018 Statistics in Archaeology. In: Loṕez Varela, S.L. (ed.) The Encyclopedia of Archaeological Sciences. Hoboken, NJ: John Wiley & Sons, Ltd. pp. 1–5. DOI: https://doi.org/10.1002/9781119188230.saseas0553.

Carrero-Pazos, M, Döhl, R, Jansen van Rensburg, J, Medici, P S and Vázquez-Martínez, A 2022 Rock art research in the digital era. Archaeology of prehistoric art. Oxford: BAR Publishing.

Challis, S, Hollmann, J and McGranaghan, M 2013 ‘Rain snakes’ from the Senqu River: new light on Qing’s  commentary on the rock art from Sehonghong, Lesotho, Azania, 46: 331–354. DOI: https://doi.org/10.1080/0067270X.2013.797135.

Chase, A S Z, Chase, D Z and Chase, A F 2017 LiDAR for archaeological research and the study of historical landscapes. In: Masini, N. and Soldovieri, F. (eds.) Sensing the past: from artifact to historical site. Cham: Springer International Publishing. pp. 89–100. DOI: https://doi.org/10.1007/978-3-319-50518-3_4.

Conkey, M W 2018 Interpretative frameworks and the study of the rock arts. In: David, B. and McNiven, I.J. (eds.) The Oxford Handbook of the Archaeology and Anthropology of Rock Art. Oxford: Oxford University Press. pp. 25–49. DOI: https://doi.org/10.1093/oxfordhb/9780190607357.013.20.

Conolly, J and Lake, M 2006 Geographical information systems in archaeology. Cambridge Manuals in Archaeology. Cambridge: Cambridge University Press. DOI: https://doi.org/10.1017/CBO9780511807459.

Davidson, I 2018 Images of animals in rock art: Not just ‘good to think’. In: David, B. and McNiven, I.J. (eds.) Oxford handbook of the archaeology and anthropology of rock art. Oxford University Press, Oxford. Oxford: Oxford University Press. pp. 435–468. DOI: https://doi.org/10.1093/oxfordhb/9780190607357.013.36.

Díaz-Guardamino, M, Sanjuán, L G, Wheatley, D and Zamora, V R 2015 RTI and the study of engraved rock art: A re-examination of the Iberian south-western stelae of Setefilla and Almadén de la Plata 2 (Seville, Spain), Digital Applications in Archaeology and Cultural Heritage, 2(2): 41–54. DOI: https://doi.org/10.1016/j.daach.2015.07.002.

Domingo, I and Gallinaro, M eds. 2021 Impacts of scientific approaches on rock art research: global perspectives. Quaternary International 572. Amsterdam: Elsevier.

Horn, C, Ling, J, Bertilsson, U and Potter, R 2018 By all means necessary – 2.5D and 3D recording of surfaces in the study of southern Scandinavian rock art, Open Archaeology, 4(1): 81–96. DOI: https://doi.org/10.1515/opar-2018-0005.

Horn, C, Pitman, D and Potter, R 2019 An evaluation of the visualisation and interpretive potential of applying GIS data processing techniques to 3D rock art data, Journal of Archaeological Science: Reports, 27: 101971. DOI: https://doi.org/10.1016/j.jasrep.2019.101971.

Jalandoni, A, Domingo Sanz, I and Taçon, P S C 2018 Testing the value of low-cost Structure-from-Motion (SfM) photogrammetry for metric and visual analysis of rock art, Journal of Archaeological Science: Reports, 17: 605–616. DOI: https://doi.org/10.1016/j.jasrep.2017.12.020.

Layton, R 1992 Australian rock art: a new synthesis. Cambridge: Cambridge University Press.

Lewis-Williams, J D and Loubser, J H N 1986 Deceptive appearances: a critique of southern African rock art studies, Advances in World Archaeology, 5: 253–289.

Martel, Á R 2019 Rock art, semiotics and meaning of. In: Encyclopedia of global archaeology. Cham: Springer International Publishing. pp. 1–8. DOI: https://doi.org/10.1007/978-3-319-51726-1_2831-1.

McCall, G S 2018 Strategies for quantitative research: archaeology by numbers. Routledge. DOI: https://doi.org/10.4324/9781315208206.

Mitchell, P 2005 Why Hunter-Gatherer Archaeology Matters: A Personal Perspective on Renaissance and Renewal in Southern African Later Stone Age Research, The South African Archaeological Bulletin, 60(182): 64–71. DOI: https://doi.org/10.2307/3889119.

Parcak, S H 2009 Satellite remote sensing for archaeology. London, New-York: Routledge. DOI: https://doi.org/10.4324/9780203881460.

Skoog, B, Helmholz, P and Belton, D 2016 Multispectral analysis of indigenous rock art using terrestrial laser scanning, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B5: 405–412. DOI: https://doi.org/10.5194/isprs-archives-XLI-B5-405-2016.

Solomon, A 1997 The Myth of Ritual Origins? Ethnography, Mythology and Interpretation of San Rock Art, The South African Archaeological Bulletin, 52(165): 3–13. DOI: https://doi.org/10.2307/3888971.

Solomon, A and Bahn, P G 2023 Rites, wrongs and analogies: religion and ritual as explanation of prehistoric rock art. In: Le Gai Scavoir. Archaeopress. pp. 274–288.

Taçon, P S C and Chippindale, C 1998 An archaeology of rock-art through informed methods and formal methods. In: Chippindale, C. and Taçon, P.S.C. (eds.) The archaeology of rock-art. Cambridge: Cambridge University Press. pp. 1–10.

Tonazzini, A, Salerno, E, Abdel-Salam, Z A, Harith, M A, Marras, L, Botto, A, Campanella, B, Legnaioli, S, Pagnotta, S, Poggialini, F and Palleschi, V 2019 Analytical and mathematical methods for revealing hidden details in ancient manuscripts and paintings: a review, Journal of Advanced Research, 17: 31–42. DOI:https://doi.org/https://doi.org/10.1016/j.jare.2019.01.003.

Van Dyke, R M 2022 Foreword. In: Zubieta, L.F. (ed.) Rock art and memory in the transmission of cultural knowledge. Cham: Springer International Publishing. pp. v–viii. DOI: https://doi.org/10.1007/978-3-030-96942-4_1.

Vinnicombe, P 1972 Myth, Motive, and Selection in Southern African Rock Art, Africa, 42(3): 192–204. DOI: https://doi.org/10.2307/1159159.

Vogels, O, Fäder, E and Lenssen-Erz, T 2021 A matter of diversity? Identifying past hunter-gatherer aggregation camps through data driven analyses of rock art sites, Quaternary International, 572: 151–165. DOI: https://doi.org/https://doi.org/10.1016/j.quaint.2020.05.057.

Wienhold, M and Robinson, D W 2018 GIS in rock art studies. In: The Oxford Handbook of the Archaeology and Anthropology of Rock Art. Oxford: Oxford University Press. pp. 787–809. DOI: https://doi.org/10.1093/oxfordhb/9780190607357.013.12.

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S45: Digitally Enabled Archeological Practice, Communication and Research: Critical reflections on evaluation and impact assessment.

Session Organisers:
Emeri Farinetti, Roma Tre University
Theodora Moutsiou, University of Cyprus
Anestis Koutsoudis, ATHENA research centre
Areti Damala, Musée des Arts et Métiers – Paris

Description

Session Format: Standard

Evaluation plays a crucial role both for cultural heritage (CH), museum and heritage studies and information technology (IT) scientists, as well as for various end users, in the context of tools, pipelines, solutions, and approaches focused on CH tasks.In their formal evaluation of public archaeology, Ellenberger and Richardson (2018) emphasize the importance of evaluating and assessing public archaeology projects as a means to promote and disseminate impactful research (Moullou et al 2023), despite this area being underrepresented in academic literature (Ellenberger & Richardson 2018). However, the need to evaluate a diverse range of methodologies is not limited to public archaeology. Evaluation plays a crucial role both for cultural heritage (CH), museum and heritage studies and information technology (IT) scientists, as well as for various end users, in the context of tools, pipelines, solutions, and approaches focused on CH tasks. Finally, evaluation is capital for meaningfully engaging with various stakeholders, target groups and audiences, increasingly encompassing collaborative and citizen science approaches. (Rimvydas et al 2018). The recent EU Commission project calls and initiatives around a new European Collaborative Cloud for Cultural Heritage (ECCCH) underline that archaeological research fieldwork “produce large amounts of different kinds of data, such as survey documentation and documents presenting, narrating and interpreting the findings, photographic data, 3D models, drawings, maps and geographic information system data” (EU Commission, 2024). Furthermore, managing archaeological data requires expertise in interdisciplinary fields such as computer science and archaeology, alongside digital methodologies like database design, Geographic Information Systems (GIS) and spatial analysis, 3D reality modeling, digital twins. Within this new ECCCH it is acknowledged that data sets produced in later stages in later stages of archaeological and cultural heritage related works, become assets for cultural heritage institutions including museums, online archives, applications and plethora of new mediums.

Over the past decades, archaeological research has increasingly adopted these digital technologies to assist in excavations and field research, leading to the generation of vast amounts of archival data and documentation data (Psarros et al. 2022). As Opgenhaffen (2022) rightly points out, digital technologies are believed to enhance equal access to data and broaden inclusivity beyond archaeologists. However, the challenge of identifying and effectively reaching these broader audiences remains unresolved (Opgenhaffen 2022).

Thus, for CH and IT scientists, evaluation, quality control and assessment practices ensure that methodologies and technological solutions are effective, efficient, and scalable, while also providing data-driven insights for continuous improvement, providing opportunities for engagement with diverse audiences (Watrall 2019).

Evaluation can help verify the accuracy, reliability, and innovation of the tools and approaches used in documenting, preserving, restoring, and disseminating cultural heritage. From a researcher, end user as well as public engagement’ perspective, undertaking qualitative, quantitative and mixed methods’ evaluation is equally important, for assessing the usability, accessibility, scalability, sustainability, subjective and objective efficiency of the various tools, methodologies and datasets used and generated. Furthermore, engaging the public and gathering feedback ensures that the solutions not only meet scientific and technical standards but also resonate with and serve the needs and expectations of diverse cultural heritage communities (Ciolfi et al. 2018) and audiences, thereby enhancing the broader societal value of cultural heritage preservation efforts and magnifying their impact (Hugget 2015).

To this end, the Greek Chapter of the Computer Applications & Quantitative Methods in Archaeology (CAA-GR), which involves a wide scientific community from the Eastern Mediterranean region, proposes an insightful conference session dedicated to the convergence of humanities, archaeology, and technology, emphasizing the evaluation of projects, tools, pipelines, processes, methods, frameworks, approaches and user experiences related to the documentation, preservation, restoration, and dissemination of archaeological cultural heritage. 

This session will explore both objective and subjective evaluation strategies from the perspectives of scientists and the public, including various types of stakeholders. In particular, we seek reflective (Huggett 2015) contributions on the evaluation and impact assessment around archaeological research, practice, documentation, dissemination using the digital for diverse end users, audiences and stakeholders (Walcek et al 2016). 

We therefore welcome works on: 

  • The evaluation of archeological practices, from excavation, to documentation, visualisation, 3D reconstruction, restoration, cross-linking and dissemination  
  • Reflexive procedures around everyday archaeological practice using the digital, in the field and during data analysis, documentation and interpretation processes (at any stage of the life-cycle of a project)
  • Applications and digital products related to the visualization and dissemination and public engagement on both tangible and intangible Cultural Heritage 
  • Public engagement and community practices and their short, medium and long term impact
  • Stakeholders, end users and community (public) engagement practices and their impact
  • Reflections on the meaning and method of evaluation and its impact on the epistemological, ethical and practical goals of Archaeology

Discussions will highlight the significance of these evaluation procedures in ensuring the effectiveness and relevance of preservation efforts, fostering a comprehensive understanding of cultural heritage, and enhancing public engagement and education.

References  

Ellenberger, K., & Richardson, L.-J. Reflecting on Evaluation of Public Archaeology. Online Journal in Public Archaeology, 2018, 8, 65–94.

EU Commission 2024, A European Collaborative Cloud for Cultural Heritage – Innovative tools for documenting, interlinking and organising data, available at: https://www.horizon-europe.gouv.fr/european-collaborative-cloud-cultural-heritage-innovative-tools-documenting-interlinking-and-37299

Opgenhaffen, L.. Archives in action. The impact of digital technology on archaeological recording strategies and ensuing open research archives. Digital Applications in Archaeology and Cultural Heritage, 2022, 27, e00231.

Psarros, D., Stamatopoulos, M. I., & Anagnostopoulos, C. N. . Information Technology and Archaeological Excavation: A Brief Overview. 2022, https://doi.org/10.5281/ZENODO.6323149

Laužikas, Rimvydas, Dallas, Costis, Thomas, Suzie, Kelpšienė, Ingrida, Huvila, Isto, Luengo, Pedro, Nobre, Helena, Toumpouri, Marina and Vaitkevičius, Vykintas. “Archaeological Knowledge Production and Global Communities: Boundaries and Structure of the Field” Open Archaeology, vol. 4, no. 1, 2018, pp. 350-364. https://doi.org/10.1515/opar-2018-0022

Luigina Ciolfi, Areti Damala, Eva Hornecker, Monika Lechner, Laura Maye (Eds), Cultural Heritage Communities Technologies and Challenges. Routledge, London, 2018.

Huggett Jeremy. A manifesto for an introspective digital archaeology. Open archaeology, 2015, vol. 1, no 1.

Watrall E. Building Scholars and Communities of Practice in Digital Heritage and Archaeology. Advances in Archaeological Practice. 2019;7(2):140-151. doi:10.1017/aap.2019.1

Moullou Dorina, Vital Rebeka, Sylaiou, Stella, et al. Digital Tools for Data Acquisition and Heritage Management in Archaeology and Their Impact on Archaeological Practices. Heritage, 2023, vol. 7, no 1, p. 107-121.

Averet Erin Walcek, Counts Derek, et Gordon Jody. Mobilizing the past for a digital future: the potential of digital archaeology. 2016.

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S47: Unconventional Mediterranean: digital applications to detect and survey the marginal or unexplored landscapes

Session Organisers:
Angelo Cardone, University of Bari Aldo Moro (UniBa)
Francesca Di Palma, Italian National Research Council (CNR) – Institute of Heritage Science (ISPC)
Andrea Di Meo, University of Molise (UniMol)
Alessia Brucato, University of Bari Aldo Moro (UniBa) / Italian National Research Council (CNR) – Institute of Heritage Science (ISPC)

Description

Session Format: Standard

The objective of this session is to concentrate on the non-invasive research that has recently captured the attention of marginal and relatively unknown contexts within the Mediterranean basin, the Middle East, and North Africa. The history of archaeological research includes a number of wide-ranging and substantial survey projects and excavations in the Mediterranean area. However, there has been comparatively limited attention paid to areas characterised by difficult access, a paucity of notable sites, and only marginal traces of human activity. The records include mountain, desert, and rocky areas, or ‘uncultivated landscapes’, where anthropic intervention is less recognizable as a consequence of low-impact transformations, remote positions, or scarce visibility. In fact, in recent years, remote sensing and ethno-archaeological research have enabled a notable revolution in the investigation of ‘neglected landscapes’. This is exemplified by the use of satellite images and LiDAR applications, which have markedly enhanced the utility of traditional aerial photography in the detection of archaeological traces and sites. Similarly, photogrammetry, laser scanning and geophysical surveys facilitate and speed up the documentation of preserved and buried evidence in remote and harsh environments. Moreover, the utilisation of 3D reconstructions, spatial analyses, and automatic and semi-automatic image classification techniques within dedicated software and GIS has already proved to be very efficient in assessing the potential existence of ancient sites (settlements, isolated features, burials, hunting traps, roads and paths, etc), enabling the concentration of comprehensive analyses on more feasible and circumscribed areas. Systemic theories of approach to the study of the landscape have been subject to re-evaluation throughout the ages, with a particular focus on the high integration and importance of uncultivated activities (stone and clay quarries, mines, exploitation of timber and plant products, pastoralism, etc.). This has led to an emphasis on the study of the related traces. In light of the aforementioned considerations, the objective of the session is to facilitate the advancement of research initiatives that have hitherto been overlooked in the context of the Mediterranean region. This session emphasises the importance of non invasive and digital approaches, for which proposals encompassing all historical periods are welcome, from the prehistoric era to the post-classical and modern periods. In conclusion, the aim of this session is to examine the potential of non-invasive research in such contexts, with a particular focus on critical issues, constraints and proposals for future developments. In particular, the session will consider all research activities that involve non-contact acquisition and processing of qualitative and quantitative information about archaeological or landscape features in this region. Accordingly, all research pertaining to remote sensing will be considered, including data from historical and recent terrestrial (photogrammetry and laser scanner records; dGPS and total station data acquisition; GPR, magnetometric, seismic, and georesistivimeter application; etc.), aerial (from planes and UAVs) and satellite platforms (historical cosmic photography; panchromatic, RGB, multispectral, hyperspectral and SAR imagery; LiDAR and thermal scans) and all the possible approaches, workflows and software for data processing, classification and analysis. We invite early career researchers and colleagues to submit papers focusing on the application of non-invasive methods to previously underexplored archaeological contexts in the Mediterranean, Middle East and North Africa regions, highlighting the following topics:

  • Joint or integrated use of combined sources (i.e., optical, multispectral and radar satellite imagery) and/or platforms (i.e., aerial and terrestrial survey devices);
  • Remote sensing analysis of large areas or landscape analyses;
  • Geospatial processing and post-processing using manual and automatic/semi-automatic approaches;
  • Remote sensing and computational analyses to study, monitor and preserve historical contexts or plan future activities in agreement with various institutions.
  • Geophysical surveys applied to the archaeological study;
  • The potential of photogrammetric and laser scanning surveys for the study and enhancement of archaeological sites;
  • GIS landscape analysis applied to identify areas with high potential due to the presence of settlements, sites, exploitation/catchment basins and to focus field research in targeted sample-sectors.

References

Arnoldus-Huyzendveld A., Citter, G. Pizziolo C. (2015). Predictivity – Postdictivity:a Theoretical Framework, in S. Campana, R. Scopigno, G. Carpentiero, M. Cirillo, CAA2015. Keep the revolution going. Proceedings of the 43rd Annual Conference on Computer Applications and Quantitative Methods in Archaeology, Siena, pp. 593-398.

Burri S. (2014). Reflections on the concept of marginal landscape through a study of late medieval incultum in Provence (South-eastern France), PCA-PostClassical Archaelogies, 4, pp. 7-38.

Campana S. (2014). 3D modeling in archaeology and cultural heritage. Theory and best practice, in Campana S., Remondino F. (eds) 3D Recording and Modeling in Archaeology and Cultural Heritage. Theory and best practices. BAR international series, Oxford, 2014, pp. 7-12.

Campana S., Forte M. (2006). From space to place. 2nd international conference on remote sensing in archaeology. Proceedings of the 2nd international workshop (CNR, Rome, Italy, December 4-7, 2006), Oxford 2006.

Campana S., Forte M., Liuzza C. (2010). Space, time, place. Third International Conference on Remote Sensing in Archaeology (17th-21st August 2009, Tiruchirappalli, Tamil Nadu, India), Oxford 2010.

Casana J. (2020). Global-scale archaeological prospection using CORONA satellite imagery: automated, crowd-sourced, and expert-led approaches, in Journal of Field Archaeology, 45, pp. 89–100. https://doi.org/10.1080/00934690.2020.1713285

Casana J., Goodman D. D., Ferwerda C. (2023). A wall or a road? A remote sensing-based investigation of fortifications on Rome’s eastern frontier, in Antiquity 2023, vol. 97 (396), pp. 1516-1533. https://doi.org/10.15184/aqy.2023.153

Cowley D. C. (2011). Remote sensing for archaeological heritage management, in Proceedings of the 11th EAC Heritage Management Symposium (Reykjavik, Iceland, 25-27 March 2010), Brussels, EAC, 2011.

Cozzolino M., Di Meo A., Gentile V. (2019). The contribution of indirect topographic surveys (photogrammetry and laser scanner) and GPR investigations in the study of the vulnerability of the Abbey of Santa Maria a Mare, Tremiti Islands (Italy) in Annals of Geophysics, Vol. 61, 2018. https://doi.org/10.4401/ag-7987

Dell’Unto N. (2014). The use of 3D models for intra-site investigation in archaeology, in Campana S., Remondino F. (eds), 3D surveying and modelling in archaeology and cultural heritage theory and best practices. BAR international series, Oxford, 2014.

Dimitrios D. A., Agapiou A., Hadjimitsis D., Sarris A. (2018). Remote sensing application in Archaeological Research, in Escalante-Ramírez (ed), Remote sensing – Applications, Intech 2018, pp. 435-461.

Di Meo A., Capriuoli F., Minelli A. (2024). Engineering at the service of archaeology: the CAST project applied to the Pertosa-Auletta caves, in History of Engineering, Proceedings of the 6th International Conference – Atti del 10o Convegno Nazionale, Naples, 2024 June 13th -14th, vol. 2, pp. 901- 912.

Di Palma F., Gabrielli R., Merola P., Miccoli I., Scardozzi G. (2024). Study and enhancement of the heritage value of a fortified settlement along the Limes Arabicus. Umm ar-Rasas (Amman, Jordan) between remote sensing analysis, photogrammetry and laser scanner surveys, in Proceedings of CAA 2022-2023 (in press). https://doi.org/10.5281/zenodo.11070949.

El-Baz F., Wiseman J. (2007). Remote sensing in archaeology (Interdisciplinary contributions to archaeology), New York 2007.

Fowler M. J. F. (2010). Satellite imagery and archaeology, in Cowley D. C., Standring R. A., Abicht M. J. (eds). Landscapes through the lens: aerial photograph and historic environment, pp. 99-110.

Hadjimitsis D. G., Themistocleous K., Cuca B., Agapiou A., Lysandrou V., Lasaponara R., Masini N., Schreier G. (2020). Remote Sensing for Archaeology and Cultural Landscapes. Best Practices and Perspectives Across Europe and the Middle East, Berlin.

Kaimaris D., Georgiadis C. , Patias P., Tsioukas V. (2020). Aerial and Remote Sensing Archaeology, in Apply Innovative Technologies in Heritage Science, pp. 16-40. http://dx.doi.org/10.4018/978-1-7998-2871-6.ch002

Landeschi G., Apel J., Lindgren S., Dell’Unto N. (2018). An exploratory use of 3D for investigating a prehistoric stratigraphic sequence. Proceedings of the 44th Computer Applications and Quantitative Methods in Archaeology Conference, CAA 2016 Oslo, 29 March – 2 April 2016.

Lasaponara R., Masini N. (2011). Satellite remote sensing in archaeology. Past, present and future perspective, in Journal of archaeological science, 38 (9), pp. 1195-2002. https://doi.org/10.1016/j.jas.2011.02.002

Lasaponara R., Masini N. (2012). Satellite remote sensing. A new tool for archaeology, London/New York 2012.

Leisz S. (2013). An Overview of the Application of Remote Sensing to Archaeology During the Twentieth Century, in Comer D. C. (ed), Mapping archaeological landscapes from space, pp. 11-19.

Merola P., Allegrini A., Guglietta D., Sampieri S. (2006). Study of buried archaeological sites using vegetation indices, in Remote Sensing for Environmental Monitoring, GIS Application, and Geology VI, vol 6366 (2006), pp. 64-75. https://scholar.google.com/scholar?cluster=12271873668449455358&hl=en&oi=scholarr

Merola P., Allegrini A., Guglietta D., Sampieri S. (2006). Buried archaeological structures detection using MIVIS hyperspectral airborne data, in Infrared Spaceborne Remote Sensing XIV, vol. 6297 (2006), pp. 272-283. https://www.spiedigitallibrary.org/conference-proceedings-of-spie/6297/62970Z/Buried-archaeological-structures-detection-using-MIVIS-hyperspectral-airborne-data/10.1117/12.681522.short

Notarian, M. (2020). Introduction to the Special Issue on 3D Methodologies in Mediterranean Archaeology. Studies in Digital Heritage, 4(2), 75–77. https://doi.org/10.14434/sdh.v4i2.32095

Gojda M. (2020). Air survey and remote sensing in archaeology, Warszawa 2020.

Parcak S. (2009). Satellite remote sensing for archeology, London/New York 2009.

Scardozzi G. (2016). An introduction to satellite remote sensing in archaeology: state of the art, methods, and applications, in Boschi F. (a cura di) Looking to the future, caring for the Past. Preventive archaeology in theory and practice. Proceedings of the 2013-2014 Erasmus IP Summer Schools in Preventive Archaeology: evaluating sites and landscapes. Methods and techniques for evaluating the archaeological value, pp. 217-239.

Siegel, O. (2022). Reevaluating the Role of Inter-Polity Boundaries (tASw) in Middle and New Kingdom Egypt, accepted by the Journal of Egyptian History 15 (2022): 1-42.

Siegel, O., Bogdani, J., Urcia, A., Nicolini, S., & Gatto, M. C. (2024). The BORDERSCAPE Project WebGIS: State Formation and Settlement Patterns near the Ancient Egyptian Southern Border, in Journal of OpenArchaeology Data. DOI: https://doi.org/10.5334/joad.125.

Tapete D. (2018). Remote Sensing and Geosciences for Archaeology, in Geoscience, 8 (2), pp. 1-10. https://doi.org/10.3390/geosciences8020041.

Verhagen, J. W. H. P., Whitley, T. G. (2020). Predictive Spatial Modelling. In Gillings M., Hacıgüzeller P., & Lock G. (eds.), Archaeological Spatial Analysis: a Methodological Guide, London, pp. 231-246. https://doi.org/10.4324/9781351243858-13.

Wang Y., Wu L., Gao F., Gao C., Wang X. (2013). A Summary of Remote Sensing Environmental Archaeology in the Study of Ancient Settlements, in Information Tchnology Journal, 12 (22), pp. 6777-6782. https://doi.org/10.3923/itj.2013.6777.6782.

Wang Y., Liu Y. (2024). Development Trend of Remote Sensing Archaeology Based on Scientific Literature, in Electronic Engineering and Informatics, vol. 51, pp. 247-254. http://dx.doi.org/10.3233/ATDE240083

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S48: Merging Two Realities: Integrating Mixed Reality (MR) and Gamification in On-Site Archaeological Projects

Session Organisers:
Murat Taskiran, Pamukkale University
Asuman Lätzer-Lasar, Philipps-University Marburg
Ecem Akkaya, Akdeniz University
Emre Çoban, Pamukkale University

Description

Session Format: Standard

The narration of the history of ancient sites is a crucial aspect of archaeological discourse. Given the continually evolving nature of the field, driven by the constant generation of new data and knowledge, it is essential for archaeologists to promptly disseminate their latest insights to a wide range of audiences. In recent years, a variety of digital methodologies, such as Virtual Reality (VR) and Augmented Reality (AR) have been increasingly employed at archaeological sites to enhance both research outcomes and public engagement (Jacob and Nóbrega 2021). This is not yet the case with approaches such as Mixed Reality (MxR), which offer a distinctive opportunity to merge real and virtual worlds, thereby creating novel environments and visualizations in which physical and digital objects coexist and interact in real time (Bekele 2021). Until now, mixed reality projects have been predominantly used in enclosed settings, such as museums (Barrile et al. 2022). As virtual reality (VR) and augmented reality (AR) applications become more prevalent in the preservation, protection, and collection of cultural history at sites, the operationalization of mixed reality has the potential to enhance the learning process, motivation, and understanding of specific events and historical elements for students, tourists, and experts alike (Ioannides, Magnenat-Thalmann, and Papagiannakis 2017, 371). Accordingly, this session invites papers that present projects and studies employing these methods in the field, with a particular focus on original excavation sites. The objective of our session is to foster discussions on the advantages of these technologies, while also addressing the challenges and uncertainties associated with their application.

Augmented Reality (AR) and Virtual Reality (VR) have revolutionized archaeological practice by merging digital technologies with physical spaces, creating immersive and interactive experiences for both researchers and the public. AR, for instance, allows for the overlay of digital reconstructions onto physical ruins, enabling users to visualize ancient structures and artifacts in their original form (https://ar-route.de). This dynamic approach not only engages visitors but also preserves the authenticity of the site, offering a unique way to experience historical narratives without physically altering the landscape (Reilly 1990). Similarly, VR has transformed archaeological exploration by enabling the virtual reconstruction of sites that are either endangered or inaccessible. This technology allows users to navigate historical settings in ways that traditional methods cannot replicate, making it a powerful tool for both educational and preservation efforts (Dieb, Alsalloum, and Webb 2024). In addition, VR facilitates new forms of analysis by simulating past environments and interactions, offering insights into spatial dynamics and social organization that are otherwise difficult to capture (Ch’ng, Stone, and Arvanitis 2005).

Various studies indicate that didactic methods for the dissemination of knowledge are often enriched by the use of artificial figures, such as avatars, which are frequently employed in museums and educational materials to effectively engage broader audiences (Spallone et al. 2024). The advent of digital methods and devices has made it possible to create avatars that can be used directly on site. By simulating human behavior, these avatars can be utilized to create interactive and memorable experiences, which in turn can help to deepen the users’ understanding of historical contexts (Jacob & Nóbrega, 2021). Moreover, digital human technologies — encompassing VR, AR, artificial intelligence (AI), and simulation tools — merge the physical with the digital world, thereby offering a more comprehensive and engaging exploration of history.

The integration of game engines, digital humans, AR, and original archaeological sites offers a multisensory, immersive experience. These technologies simulate historical situations, allowing for the re-enactment or re-enlivening of past events, thereby offering users an unprecedented opportunity to engage with history as though they were present in another time. In this way, digital humans, for instance, act as bridge between the past and the present by telling a narrative about the place its people and history. However, alongside these advantages come technical and ethical considerations when employing mixed realities methods, which will also be addressed during the session.

  • What types of mixed reality tools and approaches do you utilize on site?
  • What are the advantages and challenges associated with these tools and approaches?
  • Which ethical implications have you encountered? Such ethical implications may be encountered either during the process of creating virtual worlds or in the operationalization of these environments in the field, when merging the two realities.

References

Barrile, Vincenzo, Ernesto Bernardo, Antonino Fotia, and Giuliana Bilotta. 2022. “A Combined Study of Cultural Heritage in Archaeological Museums: 3D Survey and Mixed Reality.” Heritage 5 (June):1330–49. https://doi.org/10.3390/heritage5030069.

Bekele, Mafkereseb Kassahun. 2021. “Mixed Reality:” In Virtual Heritage, edited by Erik Malcolm Champion, 93–104. A Guide. Ubiquity Press. http://www.jstor.org/stable/j.ctv2dt5m8g.12.

Ch’ng, Eugene, Robert Stone, and Theodoros Arvanitis. 2005. “A Virtual Reality Archaeological Framework for the Investigation and Interpretation of Ancient Landscapes.” In Proceedings of the IASTED International Conference on Internet and Multimedia Systems and Applications, EuroIMSA, 532.

Dieb, Rida, Ataa Alsalloum, and Nicholas Webb. 2024. “Interactive 360° Media for the Dissemination of Endangered World Heritage Sites: The Ancient City of Palmyra in Syria.” Built Heritage 8 (1): 18. https://doi.org/10.1186/s43238-024-00126-3.

Ioannides, Marinos, Nadia Magnenat-Thalmann, and George Papagiannakis, eds. 2017. Mixed Reality and Gamification for Cultural Heritage. 1st ed. 2017. Cham: Springer International Publishing: Imprint: Springer. https://doi.org/10.1007/978-3-319-49607-8.

Jacob, João, and Rui Nóbrega. 2021. “Collaborative Augmented Reality for Cultural Heritage, Tourist Sites and Museums: Sharing Visitors’ Experiences and Interactions.” In Augmented Reality in Tourism, Museums and Heritage, edited by Vladimir Geroimenko, 27–47. Springer Series on Cultural Computing. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-70198-7_2.

Reilly, Paul. 1990. Towards a Virtual Archaeology.

Spallone, Roberta, Fabrizio Lamberti, Luca Maria Olivieri, Francesca Ronco, and Luca Lombardi. 2024. “Augmented Reality and Avatars for Museum Heritage Storytelling.” In Beyond Digital Representation, edited by Andrea Giordano, Michele Russo, and Roberta Spallone, 241–58. Digital Innovations in Architecture, Engineering and Construction. Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-36155-5_16.

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S49: GameTable: Bridging Disciplines for Heritage Games

Session Organisers:
Barbara Care, University of Fribourg
Dorina Moullou, Hellenic Ministry of Culture and Sports
Walter Crist III, Leiden University
Timothy Penn, University of Reading

Description

Session Format: Standard

Games occupy a unique position in human history, serving as both entertainment and a reflection of societal norms, values, and behaviors. While disciplines like computer science and mathematics use games to push the boundaries of AI and economic modeling, fields such as archaeology, history, and anthropology examine the deep cultural significance of games. This session seeks to bring together these diverse perspectives, focusing on the critical role games play in technological innovation, cultural preservation and education. While games are more popular than ever as a form of human entertainment, the heritage of traditional games is more threatened than ever. As the immersive qualities video and mobile games provide enticing forms of entertainment, traditional, analog forms of play which have been passed down from person to person over centuries or even millennia are becoming abandoned, and their rules become lost as playing communities disappear. Historically, many traditional games have also been lost due to the forces of colonialism, imperialism, and commercialization, which have overshadowed and erased significant parts of humanity’s game heritage. This session – organized by the COST Action (CA22145) Computational Techniques for Tabletop Games Heritage – aims to explore the reconstruction and preservation of such games, viewing them not only as leisure activities but as repositories of cultural richness and historical narratives that are crucial for a deeper understanding of human society. By integrating perspectives from archaeology, AI, cultural studies, and museum curation, this session will also investigate how games can be revitalized as dynamic educational tools in museums and beyond. The session will promote discussions on how to harness technology to deepen our understanding of the cultural dimensions of games. Topics for Discussion:

1.Reconstructing Historical Games:

  • Methodologies for reconstructing and preserving games that have been partially lost or forgotten.
  • Techniques for reconstructing missing rules and gameplay mechanics in incomplete games, utilizing both AI and archaeological evidence.

2. AI Applications in Studying Heritage Games:

  • How AI can simulate historical gameplay, aiding in the understanding of game evolution and player behavior.
  • AI-driven methods for identifying and studying unrecognized games across different regions and historical periods.

3. Games in Museums:

  • Integrating games into museum exhibits as interactive educational tools that engage visitors in learning about cultural and historical contexts.
  • Digital curation practices for preserving and displaying heritage games in museums, including virtual exhibits and immersive experiences.
  • Collaborations between museums, archaeologists, and technologists to bring historical games to life for public audiences.

4. Games as Educational Tools:

  • Using reconstructed and preserved games to teach cultural, historical, and technological concepts in both formal and informal education settings.
  • Developing digital platforms that make heritage games accessible and engaging for educational purposes, particularly in museums and classrooms.

5. Heritage Game Preservation and Community Engagement:

  • Exploring the role of museums and digital initiatives in safeguarding and revitalizing traditional games from underrepresented cultures.
  • Involving local and global communities in the digital preservation and study of games,
  • Strategies for crowdsourcing knowledge and resources in the reconstruction and preservation of heritage games, including collaboration with museums.

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S50: Exploring the Nexus of Robotics and Archaeology: Unveiling the Potential, contribution and Ethical Dimensions in different research fields

Session Organisers:
João Marreiros, Leibniz Association
Arianna Traviglia, Istituto Italiano di TecnologiaOxford

Description

Session Format: Standard

In the past decades, robots have woven their threads across diverse domains, functioning as integral components. Spanning healthcare, manufacturing, agriculture, and industries, robots are the linchpin that sustains and advances numerous systems. Notably, the field of archaeology has also embraced these mechanical collaborators, testing ways to employ them on archaeological sites, within laboratory studies, and even in public exhibitions. These robotic allies range from automated machines performing cultural heritage manipulation and scanning to unmanned aerial (UAVs) or underwater (ROVs) vehicles that probe depths and spaces beyond human reach, to operating laboratory-controlled experiments to test archaeological-like materials and artefacts, increasing the efficiency and reliability of archaeological and conservation practice endeavors. In tandem with this, digital workflows and AI-driven algorithms are rapidly transforming data interpretation, site modeling, and artifact analysis, accelerating discoveries and enhancing documentation practices. However, amidst these accomplishments, a question arises: can we catapult robots to new heights within archaeology and the field of Cultural Heritage at large, perhaps merging them with Artificial Intelligence, to craft an “Artificial Archaeologist”? This dynamic session delves into the current landscape of robotics within the Archaeology and Cultural Heritage domain, pushing the boundaries of possibility into the foreseeable future research avenues. We invite thought-provoking proposals encompassing a spectrum of insights from different archaeological research fields, spanning both concrete case studies and theoretical reflections. Our exploration encompasses multiple dimensions:

  • the role of robots in archaeological practice: archaeologists have harnessed robotic technology across various scenarios. This session seeks to unveil the nuances of these interactions. What are the contexts in which robots prove indispensable, and what challenges do they alleviate? How do these mechanical aids impact archaeological processes, amplifying the precision of data collection, analysis, and preservation? Do the convergence of robotics with digital and computational systems, such as 3D scanning, GIS mapping, and databases, enhances the scope and reliability of archaeological research? Contributions on practical applications, from data collection during fieldwork to laboratory analysis, are invited to enrich the discourse.
  • robots and the act of excavation: an intriguing discourse revolves around the notion of robots as ‘fieldwork companions’. Could robots assume the role of human archaeologists in the excavation process? By integrating robotics with computational modeling, can we simulate different excavation/survey scenarios, improving our approach to delicate, large-scale, or hazardous sites? We aim to deliberate on the potential benefits and implications of this prospect, spanning efficiency gains, preservation of archaeological sites, and even the reshaping of archaeological narratives.
  • robots as architects of archaeological knowledge: another compelling avenue to explore is the fusion of robotics with knowledge-building endeavours. How might robots serve as tools for processing voluminous data, and constructing comprehensive archaeological narratives? We welcome explorations of how robotic technologies can augment the archaeological discipline, aiding in generating insights and perspectives previously unattainable.
  • ethical considerations in robotic archaeology: the surge of robotic engagement in archaeological practice mandates a critical examination of ethical dimensions. What concerns arise when technology interweaves with cultural heritage preservation? This session aspires to stimulate conversations on ethical implications such as data ownership, the potential displacement of human expertise, and the preservation of archaeological integrity.

Digital computation and robotic integration offer vast, yet uncharted territory for archaeological research, extending the capabilities of human researchers. This session seeks to map the contours of this evolving collaboration, unravelling its current standing and paving a path towards its future potential.

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S51: Bridging the gap between theory and practice: Teaching digital fieldwork archaeology

Session Organisers: Pawel Lech, University of Warsaw
Martina Seifert, University of Hamburg
Nikola Babucic, University of Hamburg
Łukasz Miszk, Jagiellonian University

Description

Session Format: Standard

Digital archaeology has revolutionized the way to conduct fieldwork offering innovative methods for survey, documentation, analysis, and the preservation of archaeological sites. Incorporating digital tools into archaeological fieldwork has allowed for greater precision, efficiency, and enhanced data interpretation. As we move into an era where technology is integral to cultural heritage protection, it is crucial to equip the next generation of archaeologists with the skills and knowledge needed to use these advanced methods effectively. This session proposal seeks to bring together experts in digital archaeology to explore and exchange knowledge about the teaching of modern fieldwork methods. The focus will be on integrating a wide range of technologies into the practical training of students and professionals alike, covering geophysical prospection, remote sensing, 3D documentation, excavations, and digital documentation through GIS and WebGIS platforms. Key themes include expanding the digital horizons of fieldwork, applying non-invasive techniques in archaeological research, and promoting digital methods for heritage protection. By equipping students with these skills, we ensure they are well-prepared to navigate the increasingly digital landscape of archaeology, fostering a new generation of archaeologists adept at using cutting-edge technologies to preserve and interpret the past. Despite the success of digital archaeology training programs, several challenges can arise during field schools and seminars that must be addressed. One of the most significant difficulties is the complexity of the technology itself. Operating advanced geophysical equipment or UAVs requires a steep learning curve, and without proper instruction, students may struggle to collect high-quality data. Moreover, the interpretation of geophysical and remote sensing data can be daunting for those unfamiliar with the software and analytical processes. This session would like to invite papers that include a variety of teaching approaches and encourage a discussion on best practices in the field with a focus on the sustainable transfer of knowledge for archaeologists.

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S52: Computational interfaces: Exploring the Potential of Application Programming Interfaces (APIs) and Domain-Specific Languages (DSLs) in Archaeology

Session Organisers:
Martin Hinz, University of Bern
Clemens Schmid, Max Planck Institute for Geoanthropology Jena

Description

Session Format: Standard

The CAA Special Interest Group “Scientific Scripting Languages in Archaeology” (SSLA) invites submissions for a session on the emerging potential of computational interfaces for archaeological research data and tools. This session aims to explore how Application Programming Interfaces (APIs), Command Line Interfaces (CLIs) or Domain-Specific Languages (DSLs)— collectively referred to as computational interfaces—can reduce the complexity of computational processes and can empower archaeologists to conduct more reproducible, transparent, and efficient research.

Background and Rationale

As archaeology continues to embrace digital technologies, the need for reproducible research has become more pressing. Scripting languages are essential for this, providing archaeologists with the ability to automate workflows, reproduce analytical processes, and share methods transparently across the discipline. However, many archaeologists may refrain from adopting scripting languages due to the steep learning curve, lack of institutional and pedagogical support, and — perhaps most importantly — an inability to relate abstract computational processes to actual archaeological use-cases. APIs, CLIs, DSLs and other programming interfaces built for (and by) archaeologists offer a unique potential to address this difficulty by providing structured, machine-readable workflows and commands that match archaeological concepts and nomenclature, while simultaneously ensuring that even complex analytical tasks can be performed transparently and consistently. These interfaces therefore serve as bridges between archaeologists and the powerful world of scripting-based computational tools. However, while APIs have already begun to play a significant role in archaeology, enabling the integration of diverse digital resources, the development and application of Command line interfaces is lagging behind, and Domain-Specific Languages remain largely unexplored. DSLs are specialized programming languages tailored to the requirements of a particular field or task. They are often not computationally universal, i.e. able to implement any algorithm, but instead only model a narrow target domain. Many are embedded as libraries in a host language (eDSLs) to reuse syntax and compiler of the latter. While tools like OxCal have already incorporated DSL-like features for radiocarbon dating and chronological modeling (Bronk Ramsey, 2009), there is a significant opportunity to expand the use of DSLs across other areas of archaeological research: They could streamline processes such as spatial analysis, excavation data management, and artifact classification, allowing archaeologists to focus more on their research questions and less on the technical complexities of the tools they use. By creating languages that align closely with the terminology and workflows of archaeology, DSLs could simultaneously make sophisticated methods like Bayesian analysis, predictive modeling, and data science more accessible to archaeologists who may not have a background in computer science. CLIs are a more basic programmable interface. They allow access to the functionality of a software tool by calling it with a set of parameters on the command line. They thus share some of the potential described for DSLs and generally come at a lower cost both for developers and users, because they are easier to implement, run and learn. While they guarantee reusability and interoperability between tools, they also lack some of the advanced abilities of DSLs to empower users to express complex models and workflows. APIs, finally, have already demonstrated their value in archaeology by facilitating the integration of various tools and datasets. APIs provide standardized interfaces that allow different software systems to communicate with each other, for example over the internet, enabling archaeologists to combine data from multiple sources, such as GIS platforms and archaeological databases, in a seamless and efficient manner. The use of APIs has proven effective in enhancing data interoperability and enabling collaborative research across different institutions and disciplines. However, while APIs have made significant strides in improving data access and integration, they still require users to understand the underlying systems and data structures they interact with. This is where CLIs and DSLs could complement APIs, providing a higher level of abstraction that allows users to perform complex tasks without needing to engage with technical details. The development of computational interfaces in archaeology is a desideratum, offering the potential to revolutionize how archaeological data is processed, analyzed, and interpreted. By focusing on APIs, CLIs and DSLs, this session seeks to explore the possibilities for creating or adapting languages, both free-standing or embedded, to meet the unique needs of archaeological research.

We encourage submissions that explore various aspects of computational interfaces in archaeology, including their development, potential applications, and integration with existing tools. Suggested topics include:

The Case for Programming Interfaces in Archaeology: Discussions on the need for and potential benefits of developing APIs, CLIs and especially DSLs tailored to archaeological research, including how they could simplify complex analyses and make advanced tools more accessible to non-specialists.

Development of Interfaces: Insights into the design and development of interfaces for archaeology, focusing on how their inherent languages can be created to align with the specific needs and workflows of the field. Key technical challenges of DSLs include for example parsing (transforming code into expressions), evaluation (handling domain logic), tooling (supporting program development), and error messages, with interest in user and developer perspectives on these issues.

Current Examples and Future Directions: Exploration of existing tools that provide APIs or CLIs – or incorporate DSL-like features, such as OxCal. Including discussion of how these tools could be expanded or new systems developed to address other areas of archaeological research.

The Interplay of Computational Interfaces: Papers that examine how interfaces can complement each other by facilitating data integration and interoperability, enabling them to function more effectively within the broader ecosystem of archaeological software.

Interdisciplinary Collaboration: Examples of how collaborative efforts between archaeologists, computer scientists, and other specialists can enhance or can be enhanced by developing interfaces that meet the unique needs of archaeological research.

This session offers a platform for both experienced researchers and emerging scholars to share their insights and ideas. We encourage submissions that focus on the potential and challenges of developing DSLs for archaeology, as well as those that explore the role of APIs, CLIs or other computational interfaces. We welcome live-coding in the presentations.

Reference

Bronk Ramsey, C. (2009). “Bayesian Analysis of Radiocarbon Dates.” Radiocarbon, 51(1), 337-360.

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S53: Not Just Pretty Pictures: Utilizing 3D Scans for Precise Data Collection in Archaeology

Session Organisers:
Vojtech Nosek, Masaryk University
Martin Kostal, Masaryk University

Description

Session Format: Standard

In archaeology, 3D scanning has revolutionized the way we see, document and analyze artifacts, providing detailed visualizations that surpass traditional methods. However, the value of these scans goes beyond producing visually appealing digital replicas. The true power of 3D scanning lies in its potential to yield precise, quantifiable data about artifacts. By focusing on extracting accurate measurements—such as dimensions, surface textures, and volumetric properties—researchers can gain deeper insights into the manufacturing techniques, usage, and wear patterns of ancient objects. When approached scientifically, 3D scans offer high-resolution data that can be analyzed statistically, allowing for robust comparisons between artifacts from different sites or periods. This section expands on this by exploring the characteristics of 3D models and the extraction of both qualitative and quantitative data for further scientific applications. The goal is to evaluate the different types of 3D models used in archaeology, investigate how to effectively extract data from them, and explore their use in the interpretation of the past. Archaeology primarily utilizes two types of 3D models: documentary (scans) and reconstructive models. While extracting data from documentary 3D scans is already a common practice, there remain underutilized areas—such as the analysis of micromorphology or the detailed study of color information encoded in 3D textures. Reconstructive models pose additional complexities. These models are often seen as merely visual representations, lacking deeper interpretative value. Yet, 3D reconstructions are, by nature, critical tools for archaeological interpretation. Since they represent spatial reconstructions, these models can be used for further analysis, such as estimating the volume of materials required for building structures or simulating physical properties like mass. Shifting the emphasis from visual appeal to the generation of empirical data enhances the potential of 3D models, transforming them into rigorous tools that drive archaeological inquiry and interpretation.”

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S54: Photorealist[ish] – Another look at appearance and 3D documentation in heritage.

Session Organisers:
Alexis Pantos, Museum of Cultural History, Oslo
Matthias Lang, University of Bonn
Tijm Lanouw, University of Amsterdam
Jitte Waagen, University of Amsterdam

Description

Session Format: Standard

Writing in 2002 Alan Chalmers (p12) writes that “Computer generated imagery indistinguishable from the real physical environment will be of substantial benefit to the archaeological community”. He goes on to stress that virtual environments that “[go] beyond the current trend of photorealistic graphics into physically and perceptually realistic scenes … are ultimately of greater use to those investigating our past.” There have been many advances in technology since this statement was made. Many in younger generations are familiar with complex responsive real-time graphics from an early age, and there has been a sea-change in the use of computer graphics in film and TV. Where once it was used to create the dramatic and the impossible, it has begun to reach a level of maturity where it can slip unnoticed into the background, indistinguishable from the physical props and actors around it in even quite mundane settings. There has also been a proliferation in the accessibility and use of 3D capture technology in archaeology and heritage in general. Nevertheless, the type of 3D data, and ways it may be used, as outlined in this statement some 23 years ago is still far from becoming routine. On the one hand, there are many technological problems that mean achieving such lofty goals remains a challenge. Reality and the human perception of it is a wickedly difficult problem and many promising technologies have fallen short of delivering on their claims. On the other hand, there are barriers within the practices of the archaeological community itself. Limitations in technical knowledge, lack of deep understanding of visual communication and the enthusiasm for adopting skills from neighboring disciplines has encouraged unrealistic expectations of technology, and inappropriate claims of the fidelity (or realism) of what can or has been achieved. Together these challenges have led to a heterogeneous landscape of digital heritage practice, poor standardization, competing approaches and variability in the quality and the aims of the material produced as highlighted a recent European wide survey (Pritchard et al 2022). Consequently, many of the concerns and frustrations outlined in Lanjouw’s 2016 exploration of digital 3D tools in heritage since the 1970’s are still familiar today. Not least of those is the “[clichéd] question of pretty pictures or research tool” (emphasis added). But as society (archaeologists included) is exposed to higher standards of computer graphics and the tools and skills to produce them increase in availability we are seeing a growing appreciation for the nuances of the material world we are documenting. With these developments the questionable binary between ‘science’ and ‘art’ that has dogged visual media in archaeology for generations is beginning to show some signs of giving way to a more rounded understanding of materiality and an understanding of the value incorporating these characteristics have for our research, our archives and the influence archaeology can have on wider society. But there are still many challenges ahead, and the path to an academically robust use of 3D where we do not feel the need to “abandon beautiful things in favour of an anti-aesthetic” (Jeffreys, 2015, p150) remains to be seen. 

We hope to host a diverse session that marries that contextualizes the latest technological workflows within solid theoretical approaches and help each other forward at a time intense technological and societal change. What aspects of materiality should we be documenting, why does it matter, and how can we do it? In particular we invite contributions on the following topics: 

  • Current and future directions of 3D documentation of objects with complex material appearance 
  • Latest approaches to data collection and visualization in 3D such as NeRF’s, Gaussian Splats and integrated BRTF capture systems to PBR 
  • Robust and standardized pipelines of 3D documentation
  • Interoperability of 3D data (both technical and cultural)
  • Long-term and sustainable storage of complex 3D data
  • Theoretical and forward-looking presentations that consider the tole 3D data produced by heritage institutions in emerging digital landscapes/marketplaces.

References

Chalmers, A., 2002. Very realistic graphics for visualising archaeological site reconstructions, in: Proceedings of the 18th Spring Conference on Computer Graphics. Presented at the PCK50: Principles of Computing Knowledge: Paris C. Kanellakis Memorial Workshop, ACM, Budmerice Slovakia, pp. 7–12. https://doi.org/10.1145/584458.584460

Lanjouw, T., 2016, “Discussing the obvious or defending the contested: why are we still discussing the ‘scientific value’ of 3D applications in archaeology?” in Congrès international des sciences préhistoriques et protohistoriques, Congrès international des sciences préhistoriques et protohistoriques (Eds.), 2016. The three dimensions of archaeology: proceedings of the XVII UISPP World Congress (1-7 September 2014, Burgos, Spain), Archaeopress archaeology. Archaeopress Publishing Ltd, Oxford.

Jeffrey, S., 2015. Challenging Heritage Visualisation: Beauty, Aura and Democratisation. Open Archaeology 1, 144–152. https://doi.org/10.1515/opar-2015-0008

Pritchard, D., Rigauts, T., Ripanti, F., Ioannides, M., Brumana, R., Davies, R., Avouri, E., Cliffen, H., Joncic, N., Osti, G., Toumpouri, M., 2021. STUDY ON QUALITY IN 3D DIGITISATION OF TANGIBLE CULTURAL HERITAGE, in: Proceedings ARQUEOLÓGICA 2.0 – 9th International Congress & 3rd GEORES – Geomatics and preservation. In, Editorial Universitat Politécnica de Valéncia. https://doi.org/10.4995/arqueologica9.2021.12113

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S55: Computational models concerning climate change and its effect on cultural heritage assets

Session Organisers:
Anno Hein
Ioannis Karatasios
Mandy Vlachogianni
Dimitris Egglezos
Dorina Moullou

Description

Session Format: Standard

The conservation and preservation of cultural heritage collections and monuments in the context of changing environmental conditions due to the ongoing climate change is one of the most urgent issues to be considered in the preservation and conservation of cultural heritage. In order to design appropriate and effective mitigation strategies for protecting cultural heritage assets -such as archaeological sites, monuments and historic buildings- it is critical to understand the complex interactions between intrinsic material properties and microclimate conditions. These interactions span multiple scales, from deterioration phenomena at molecular-scale level to mechanical loadings associated with the performance of building materials and components at the macro-scale level. Addressing this complexity requires the integration of various computational models, including structural multiscale models using the Finite Element Method (FEM), environmental/climatic models for simulate the changing extrinsic conditions and constraints as well as durability studies and Life Cycle Analysis models. These models must be evaluated and assessed particularly considering the modifications of microstructural characteristics after different conservation interventions.

The integration of climate models in structural and material simulations not only enhances the physical preservation of artifacts and monuments but also contributes to the development of sustainable, data-informed heritage management strategies. This approach holds potential in providing a new layer of understanding in the study of complex deterioration mechanisms, their progression, and cumulative effects on the  materials of heritage collections and monuments. Moreover, these models serve as valuable tools for decision-makers, offering predictive insights into future climate impacts, prioritizing interventions, and optimizing resource allocation for conservation efforts.

This session encourages interdisciplinary collaboration, bringing together expertise from archaeology, materials science, conservation, environmental science, engineering and data science.

In the above context, this session welcomes papers in the following topics: 

  • Microstructural and meso-scale modeling and simulation of deterioration processes and the efficacy of conservation treatments under different climate scenarios
  • Structural macro-scale modelling for vulnerability and risk assessment of artifacts and monuments
  • Prediction models for visualization and quantification of durability and deterioration phenomena
  • Climate impact on the seismic vulnerability of monumental structures 
  • Environmental models predicting constraints
  • Climate models
  • Machine Learning Models for assessing conservation interventions

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S46: Advances in Computational Archaeology (General Session)

Session Organisers:
Lisa E. Fischer, CAA Chair
Jeffrey Glover, Georgia State University

Description

Session Format: Standard

Do you have a computational archaeology topic or project to present outside of the scope of one of the existing sessions? Are you engaged in cutting-edge research on geophysics, data management, visualization techniques, semantic web, or another digital archaeology topic that you would like to share? For the ease of the review process, please select the most closely related topical session as your primary choice when uploading in the CMT submission system. Then select this session as the secondary option to indicate that you feel that your paper is not a strong fit for the primary one chosen. Papers accepted into the “Advances in Computational Archaeology” session for the final program will be grouped thematically, as practical, to create related blocks of papers.

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