Programme

COMING SOON

Sessions

S01: iN Deep: Cultural Presence in Immersive Educational Experiences (Other)

Elaine A Sullivan, University of California Santa Cruz

Sara Perry, Museum of London Archaeology

Paola Derudas, Lund University

Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (XR) technologies are increasingly incorporated into university classrooms and public education in the GLAM sector (galleries, libraries, archives, and museums). The potential to use these technologies to engage students and the public with archaeological knowledge (such as site reconstructions, artefacts, or re-imagining the activities of past peoples) is exciting, but these forms of representation, including the use of individual headsets, tablets, and personal mobile phones, come with particular challenges. In his book Critical Gaming (2015), Eric Champion argued that virtual realities should express ‘cultural presence,’ the meaning and significance of a time, place, or object to people of the past. Hyper-reality, photogrammetry, and ever-increasing levels of ‘accuracy’ in 3D models do not inherently convey aspects of cultural significance and meaning, and many VR/AR/XR experiences fall dramatically short of the goal of expressing the importance of past places and things to
their original communities. Emphasis on technological and (especially) hardware innovation often deflects attention from critically engaging with questions of meaning-making.
This panel asks those creating or intensely using Archaeology VR/AR/XR to focus NOT on software, hardware, or the latest technical innovations, but on how we as archaeologists
can better design, create, or curate experiences that inspire and educate students and the public on the cultural importance of archaeological spaces, objects or themes.

What are successful techniques to aid a visitor to better understand the original context of an object now placed in a (often far off) museum or gallery? How can university instructors
incorporate the (problematically individual) headset or mobile experiences into pedagogy to provide meaningful and active student learning? How can complex data be usefully layered or curated so that multiple types of museum visitors or classes could find it
informative and emotionally resonant? How can we turn these increasingly popular technologies into serious spaces of cultural learning and curiosity, moving beyond the initial ‘wow’ factor

Format
Instead of traditional 20 minute talks, we request that participants present 8-10 minutes in depth on one VR/AR/XR experience they have designed and/or utilized in a university or GLAM setting (not a general review of multiple types of work). We ask
participants to present and explain aspects of design and interaction and their intent in that experience; or, if the content was not designed by the presenter, how content was incorporated, curated, or enhanced for the classroom or GLAM experience. Specifically,
we ask presenters to think thoughtfully and critically about how we might collectively learn to use these technologies in more informed ways, including: What types of interactions with students or the public have shown promise, and how might we build on those successes? What practices have not worked, and how might we learn from our failures? What particular aspects of archaeological and cultural heritage knowledge are best emphasized in the VR/AR/XR experience? What is key to re-using content created by others, including content created by non-archaeologists?

The session will be divided into four sections:

  • 1st group of presentations, ~five presenters (10 minutes per presentation)
  • a ~30 minute ‘hands-on’ period** where participants and the audience will be able to engage/interact directly with the presented content from both presentation groups
  • 2nd group of presentations, ~five presenters (10 minutes per presentation)
  • concluded by a ~30-minute Q&A session for the full group of presenters and audience

We hope this format will allow the audience to engage directly with the content before opening up the session for questions and comments. The goal is to turn this session into a workshop that helps all present work more critically with VR/AR/XR content and improve how we communicate scholarly information at the university and GLAM setting.

**We therefore ask participants to commit to bringing their discussed content uploaded or downloadable in some format that can be shared directly with others: including (but not limited to) VR headsets, Google cardboard, AR apps pre-installed on tablets or smart phones, etc.

References
Champion, E. (2015). Critical Gaming: Interactive History and Virtual Heritage. Ashgate Publishing, Ltd.

S03: Quantitative approaches applied to lithic studies (Standard)

João Carlos Moreno de Sousa, Universidade de São Paulo

Mercedes Okumura, Universidade de São Paulo

Judith Charlin; CONICET-Universidad de Buenos Aires

Since Albert Spaulding's (1953) classic paper that introduced modern statistical thinking to Archaeology, many theoretical and methodological developments have been used in order to further understand questions related to diversity, function, style, as well as identity and cultural boundaries among past human groups. No doubt that lithic materials are the most well preserved and conspicuous remains observed in precolonial archaeological sites all over the world. Quantitative methods are those that manipulate numbers and use measurement in the research process (Aldenderfer 1998:93), such methods can be applied to either quantitative or qualitative variables. The union between quantitative methods and lithic analyses have been important to allow archaeologists to handle the vast amount of data that can be generated through the several different approaches applied to describe, summarize, and interpret such materials, including hypothesis testing. Important topics for lithic research, like raw material procurement, tool manufacture, assemblage variability, as well as tool use and behavioral questions (Odell 2004) can be properly addressed using a myriad of quantitative methods from descriptive to inferential statistics, including multivariate models. Technological analyses of lithic assemblages and the subsequent use of statistical approaches are usually applied to assemblages excavated from archaeological sites (including extensive surface sampling), although it can also be applied to assemblages generated by experimental archaeological studies (Moreno de Sousa 2019). In the last decades, new techniques focusing on image acquisition, visualization, modelling, and measurement of lithic materials, including laser scanning (Shott and Trail 2020) and photogrammetric approaches (Magnani et al. 2020), have allowed the creation of 3D datasets of artifacts. Besides the importance of such digital collections in terms of preservation and online access to these materials, shape analyses including traditional or geometric morphometrics (in 2 or 3D), as well as Fourier analyses can be applied to such datasets (Buchanan et al. 2014, Charlin and González-José 2012, Iovită 2010). Other quantitative approaches like Bayesian statistics have become more popular in the last two decades (Otárola-Castillo and Torquato 2018) and machine learning techniques have been recently incorporated in some projects (Elliot et al. 2021). Beyond the most popular questions regarding lithic diversity and site function, some quantitative methods have also been recently applied to address questions regarding taxonomic classification and stone tool evolution, including phylogenies of stone tools (Lycett 2011, O’Brien et al. 2001) and a combination of cladistics and shape analysis (Cardillo and Charlin 2018, Lycett et al. 2010). Quantitative methods have also been important for the study of artifact spatial variation at different scales (from intra-site to regional and latitudinal patterns), and the modeling of cultural processes across landscapes, using a combination of geoestatistics and GIS tools (Clarkson and Bellas 2014, Hodder and Orton 1976, Kintigh and Ammerman 1982). In common, many new analytical approaches need to be properly adapted to the specificities of the nature of Archaeology as a discipline, including theoretical and methodological issues (Okumura and Araujo 2019). In this session, we seek to further discussions on these important topics pertaining to quantitative methods applied to lithic analyses (ranging from traditional approaches to innovative applications, as well as a combination of both). Critical review papers, original research highlighting case studies, and other short discussion pieces are welcome. These can range from systematic reviews of specific or general topics to case studies demonstrating ways by which scholars have addressed such topics in their specific research context. Exploratory studies presenting new and innovative uses of quantitative methods applied to the analysis of lithic materials are also welcome. We hope to stimulate further discussions concerning quantitative methods applied to lithic studies and compile a resource for researchers moving forward in this area. Exploratory studies presenting new and innovative uses of quantitative methods applied to the analysis of lithic materials are also welcome. We hope to stimulate further discussions concerning quantitative methods applied to lithic studies and compile a resource for researchers moving forward in this area.

References

Aldenderfer, M. (1998). Quantitative methods in archaeology: a review of recent trends and developments. Journal of Archaeological Research, 6(2), 91-120.

Buchanan, B., O’Brien, M.J. & Collard, M. (2014). Continent-wide or region-specific? A geometric morphometrics-based assessment of variation in Clovis point shape. Archaeological and Anthropological Science, 6(2), 145-162. doi:10.1007/s12520-013-0168-x

Cardillo, M. & Charlin, J. (2018). Phylogenetic analysis of stemmed points from Patagonia: Shape change and morphospace evolution. Journal of Lithic Studies, 5(2) https://doi.org/10.2218/jls.v5i2

Charlin, J. & González-José, R. (2012). Size and shape variation in Late Holocene projectile points of southern Patagonia. A geometric morphometric study. American Antiquity, 77(2), 221-242.

S04: Hic sunt dracones! Real-world data-driven knowledge modelling resulting in Semantics and FAIR-LOD based tools and workflows (Standard)

Florian Thiery, Römisch-Germanisches Zentralmuseum, Department of Scientific IT, Mainz, Germany

Brigit Danthine, Universität Innsbruck, Department of Archaeologies, Innsbruck, Austria

Mag. Nicole High-Steskal, University for Continuing Education Krems Department for Arts and Cultural Studies

Dr. Valeria Vitale, The Alan Turing Institute

Dr. Allard W. Mees FSA, Römisch-Germanisches Zentralmuseum, Department of Scientific IT, Mainz, Germany

Dr. Karsten Tolle, Frankfurt Big Data Lab, Institute of Computer Science, Goethe-University, Frankfurt am Main, Germany

Dr. David G. Wigg-Wolf FSA, Römisch-Germanische Kommission (RGK) des Deutschen Archäologischen Institut (DAI), Frankfurt am Main, Germany, david.wigg-wolf@dainst.de

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) and enables the community to participate in the scientific discourse and create new knowledge. But 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 [4]. In 2006 Berners-Lee [2] introduced the concept of LOD, in 2018 Sanderson instigated the “Usable” aspect at EuropeanaTech [5]. Additionally, in 2016 the FAIR principles [1] were introduced: Findable, Accessible, Interoperable and Reusable.

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. Beyond them, many other networks for graph modelling in the digital humanities, such as the Pelagios Network, Linked Pasts, Graph Technologies / Graphs and Networks in the Humanities offer methods and resources that could be used and further developed for digital archaeological research.

The development of ever more repositories poses challenges in handling the complex facets of data quality and completeness. This is especially true for archaeological data, which are based on complex networks of concepts from different domains and linguistic backgrounds. Moreover, it is necessary to include means of assessing uncertainty in the data models to produce and publish transparent FAIR and LOUD data that can also describe specific stratigraphies or the (archaeological) context of objects.

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 (e.g. Alligator), modelling and reasoning on vague edges in graph data (e.g. Academic Meta Tool), creating annotated texts and images (e.g. Recogito, Annotorius), and sparql, as well as enhancing Geo-Datasets using 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.

The positive feedback on the LOD sessions on data quality, FAIR and LOUD at CAA 2017-2021 encourages the pursuit of the debate. The goal of our online session is to bring together both experts and colleagues interested in learning about FAIR and LOUD data-driven publishing and applications, as well as to collect research application scenarios to jointly promote research domain specific solutions. We would like to discuss application-oriented and data-driven investigations into how to improve technologies for FAIR and LOUD data models as a basis for reproducible and CAREful research and exchange in the Semantic Web, as well as solutions related to one or more of the issues listed below.

Issues

  • application of semantic web technologies, such as ontologies (e.g. CIDOC-CRM) or RDF, to the archaeological domain
    modelling of archaeological artefacts, 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 in order 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
  • modelling comprehensible / reproducible workflows and data flows as “Linked Pipes” [3] 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 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 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.). Only those papers will be taken into consideration which offer the data and tools involved as FAIR data and Open Source tools in Open Science repositories (e.g. Zenodo, OSF, GitHub, GiRetLab). Exceptions to this principle (e.g. dissertation in course) should be explained.

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] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018. DOI: 10.1038/sdata.2016.18.

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

[3] Thiery, F., Homburg, T. (2021). Linked Pipes @ Linked Pasts 7: Introduction. Linked Pasts VII, Ghent, Belgium. DOI: 10.5281/zenodo.5781275.

[4] Hyland, B., Atemezing, G., Pendleton, M., Srivastava, B. (2013). Linked Data Glossary, W3C Working Group Note 27 June 2013. URL: https://www.w3.org/TR/ld-glossary/.
[5] Sanderson, R. (2018). Shout it Out: LOUD by Rob Sanderson, EuropeanaTech Conference 2018. URL: https://de.slideshare.net/Europeana/shout-it-out-loud-by-rob-sanderson-europeanatech-conference-2018-98225909

S05: Our little minions IV: small tools with major impact (Other)

Florian Thiery, Römisch-Germanisches Zentralmuseum, Department of Scientific IT, Mainz, Germany

Moritz Mennenga, Lower Saxony Institute of Historical Coastal Research, Wilhelmshaven, Germany

Ronald Visser, Saxion University of Applied Sciences, Deventer, Netherlands

Brigit Danthine, Universität Innsbruck, Department of Archaeologies, Innsbruck, Austria

In our daily work, small self-made scripts (e.g. Python, R, Bash), home-grown small applications (e.g. GIS Plugins) and small hardware devices significantly help us to get work done. These little helpers -“little minions” [4] – often reduce our workload or optimise our workflows, although they are not often presented to the outside world and the research community. 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, and 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 and – perhaps – create spontaneously “special minion interest groups”.

As we have seen in last year’s “minion talks” since 2018 there is a wide range of tools to be shared. These may be perfect examples for your own minion creation. You can find an overview on https://littleminions.link.

At the virtual online conference CAA 2021 a lot of little minions of various research domains were published to the research community (see [1], pp. 53-55), e.g.:

  • Democratization of Knowledge from Small Museums Online Digital Collections Reusable Human and Machine-Readable Content Models by A. Avgousti, G. Papaioannou, N. Bakirtzis, and S. Hermon
  • ChronochRt –make chronological charts with R by T. Rose, and G. G. M. Girotto
  • re3dragon – REsearch REsource REgistry for DataDragons by F. Thiery, and A. W. Mees
  • geoCore - A QGIS plugin to create graphical representations of drillings by M. Mennenga, and G. Bette
  • Grading minion to the rescue by R.M. Visser
  • Introducing a stature estimation tool for human skeletal material to the public by M. Koukli, V. Sevetlidis, F. Siegmund, C. Papageorgopoulou, and G. P. Pavlidis

Format

This session invites short presentations, lightning talks – aka “minion talks” (max. 10 minutes including very short discussion) – of small coding pieces, software or hardware solutions in any status of completion, not only focusing on field work or excavation technology, associated evaluation or methodical approaches in archaeology. Each “minion 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 designed for them. In order to support the subsequent use of the tools, the goal should be, that they are open available to the scientific community (e.g. GitHub, GitLab, etc).

We invite speakers to submit a short abstract including an introduction into the tool, the link to the repository - if possible - to get access to the source code and an explanation which group of researchers could benefit from the little minion and how. The tools may address the following issues, but are not limited to: data processing tools and algorithms, measuring tools, digital documentation tools, GIS plugins, hands-on digital inventions (for excavations) and data driven tools (e.g. Linked Data, CSV, Big Data). After previous years (pt. I CAA 2018 Tübingen, pt. II CAA 2019 Krakow, pt. III CAA 2021 Limassol/virtual) 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, please send an email to us (even shortly before the conference). 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 the focus on the technical domain and also for researchers who want to get ideas about what kinds of little minions are available to help in 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 the 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 in a “CAA little minion catalogue” [2] available for the public and extended in the future on a GitHub repository at [3].

References

[1] Cyprus University of Technology (2021). CAA 2021: Digital Crossroads. Book of Abstracts. https://2021.caaconference.org/wp-content/uploads/sites/28/2021/06/CAA2021_Detailed-Programme_16June.pdf

[2] http://littleminions.link

[3] https://github.com/caa-minions/minions

[4] F. Thiery, R. Visser & M. Mennenga. (2021). Little Minions in Archaeology An open space for RSE software and small scripts in digital archaeology. SORSE - International Series of Online Research Software Events (SORSE), virtual. DOI: 10.5281/zenodo.4575167

S06: Towards an open platform for computer simulations of past socio-ecological systems (Roundtable)

Philip Verhagen, Vrije Universiteit Amsterdam

Iza Romanowska, Aarhus Institute of Advanced Studies, Aarhus University

Archaeologists are increasingly relying on computer simulations to reconstruct and understand past societies. They are successfully building and running simulations of agrarian production, trade, settlement development and movement, to name a few. The current state of the field, however, is characterised by idiosyncrasy and limited communication and integration of the community, hampering the ability of modellers to cumulatively build on each other's work. This is predominantly due to the lack of appropriate tools and platforms enabling closer integration.

To remedy this situation, the NAS2A project (Network for Agent-based modelling of Socio-ecological Systems in Archaeology; https://archaeology-abm.github.io/NASA/) is developing an open library of model algorithms and code for modelling of socio-ecological systems in archaeology. It aims to redefine current practices in collaboration and synergy in modelling communities by developing an openly available and functional models library, offering a host of elements (modules, techniques, algorithms, how-to’s/wikis etc.) as modular building blocks for elaborate and case-driven models and research questions.

In this roundtable we will present the results of the project’s first results towards developing the necessary infrastructure and standards, and invite feedback from the roundtable audience. In particular, we want to address the following questions:

  • how can we ensure that model elements can be used for a wide range of research questions?
  • how can we facilitate interaction, comparison and testing of models across platforms and programming languages?
  • how can we achieve a sustainable infrastructure for this?
  • and what more is needed to make simulation modelling accessible to a wider community of archaeologists?
S07: Cultural Heritage data across borders. Web-based management platforms for immovable cultural heritage in the global south (Standard)

Thomas Huet, University of Oxford

Crystal El Safadi, University of Southampton

Bijan Rouhani, University of Oxford

Ash Smith, University of Southampton

Cultural heritage is a "shared heritage" (UNESCO, 1945), and managing it globally - at a large scale and over a longue durée - requires gathering information from heterogeneous and disparate sources, involves the integration of different software (databases, search engines, etc.), semantic data interoperability (open international standards, multilingual thesauri, etc.), and publishing policies (URI-based names, licenses, etc.). Nowadays, such aims require IT based on the semantic web (Bikakis et al., 2021), structured as a stack of technologies (Berners-Lee, 2013), supported by the concept of FAIR principles (Findable, Accessible, Interoperable, and Reusable, Wilkinson et al., 2016) and described in Data Management Plans (DMP) along the following streams of application:

  • Data (re)use: use and reuse of data and metadata, describing sources, methods (remote sensing, ground surveys, etc.), software, format, and volume;
  • Data register: describe data and metadata by controlled vocabularies (thesauri), based on ontologies (CIDOC-CRM, XML-TEI) and presented in information placeholders like dropdown lists;
  • Data storage: database technologies (SQL, NoSQL), access policies, data versioning, backups and snapshots for short-, mid-, or long-term archives;
  • Data analysis: analyses routine and data-driven documents, database auditing, machine learning (automatic site and change detection, etc.), knowledge discovery in databases and knowledge representation;
  • Data sharing: access to publishing supports of raw or processed data or dataset through working papers, data paper (versioning), scientific papers referenced by URI-based names, how-to-cite documentation, licenses, GeoSPARQL and SPARQL endpoints.

Achieving these objectives is per se a challenge. But additionally, new challenges arise when the concerned region is the global south. Such challenges are opportunities for geospatial semantic web-based purpose-built platforms (IT capacity vs digital gap), data access rules (ethical considerations, intellectual property, etc.), multi-linguism protocols, ground/remote sensing data quality control, recording condition assessments and threats over time (Rayne et al. 2017; Andreou et al. 2020; Fisher et al. 2021).

This session welcomes papers addressing and demonstrating a successful workflow on collecting, registering, storing, analysing, and sharing knowledge on immovable cultural heritage in the global south, especially for condition and risk assessment of archaeological sites, using standard ontology. Papers should address one or more aspects of these topics, the entire workflow, or emerging issues such as web3D, image annotation, heritage BIMs. Participation is encouraged for institutional projects at the supranational and national levels, or over multi-paradigm, to inform the upcoming emerging challenges of geospatial semantic web-based purpose-built platforms over the borders.

References

Andreou, G., L. Blue, C. Breen, C. E. Safadi, H. O. Huigens, J. Nikolaus, R. Ortiz-Vazquez, and K. Westley. 2020. Maritime endangered archaeology of the Middle East and North Africa: The MarEA project. Antiquity 94 (378):e36, doi: 10.15184/aqy.2020.196

Bikakis, A., Hyvönen, E., Jean, S., Markhoff, B., & Mosca, A. (2021). Special issue on Semantic Web for Cultural Heritage. Semantic Web, 12(2), 163–167, doi: 10.3233/SW-210425

Berners-Lee, T. 2013. Semantic Web - XML2000. W3C. Accessed: 01 February 2022. Retrieved from https://www.w3.org/2000/Talks/1206-xml2k-tbl/slide10-1.html

Fisher, M., Fradley, M., Flohr, P., Rouhani, B., & Simi, F. 2021. Ethical considerations for remote sensing and open data in relation to the endangered archaeology in the Middle East and North Africa project. Archaeological Prospection, doi: 10.1002/arp.1816

Rayne, L., J. Bradbury, D. Mattingly, G. Philip, R. Bewley, and A. Wilson. 2017. From above and on the ground: Geospatial methods for recording endangered archaeology in the Middle East and North Africa. Geosciences 7 (4):100, doi: 10.3390/geosciences7040100

UNESCO (1945). Constitution of the United Nations Educational, Scientific and Cultural Organisation (UNESCO). Accessed: 01 February 2022, Retrieved from http://portal.unesco.org/en/ev.php-URL_ID=15244&URL_DO=DO_TOPIC&URL_SECTION=201.html

Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., … Others. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific data, 3(1), 1–9. doi:10.1038/sdata.2016.18

S08: Are you my type? Network analysis and the study of material culture (Standard)

Arianna Sacco, Austrian Academy of Sciences, Austrian Archaeological Institute

David Laguna Palma. University of Granada, Department of Prehistory and Archaeology

Network analysis started from sociometry, which studies the social, economic, or cultural ties of an individual, as well as how individuals link into groups and how these groups connect into a society. (Scott 2012, 7–16). Network analysis is based on the belief that interpersonal relations, as well as relations between organisations and countries, are important because they are means of transmission of behaviours, information, and goods, which travel between and because of the entities. Therefore, to understand the role and behaviour of entities (i.e. individuals, organisations), it is important to study how they interact and what relations they establish in the network (Collar 2014, 99; Collar et al. 2015, 6; Scott 2017, 2–3; Sindbæk 2013, 72–73). The network is visualised as a graph; mathematical algorithms allow us to study the role of entities and the structure of the network (e.g. Bolland 1988; Bonacich 1987; Borgatti 2005; Freeman 1979).

Archaeological studies have recently started using network analysis. It has shed new light by giving the possibility to focus on human relations and social groupings demonstrated by objects, because these relations are seen as means that allow material and non-material resources to flow between groups (Brughmans 2013, 632–33; Collar et al. 2015, 6; Mills et al. 2013, 181–82; Östborn and Gerding 2014, 76). Specifically, network analysis has been used to study relationships between individuals and groups of individuals (as in Knappett 2011, Terrell 2010), or places (as in Gjesfeld 2015; Östborn and Gerding 2014; Sindbæk 2007; Sindbæk 2013), the circulation and distribution of (types of) objects (e.g. Brughmans 2010; De Groot 2019) or even decorative features (e.g. Östborn and Gerding 2015), to understand the flow of resources (e.g. Golitko and Feinman 2015; Peeples et al. 2016), to study regionalization phenomena (e.g. Blake 2013; Coward 2010; Coward 2013), and even to study ethnic identities (e.g. Collar 2013; Collar 2014).

New ways are constantly introduced to apply network analysis to archaeological research (most recently: Brughmans 2021; Carrignon et al. 2020; Rawat et al. 2021; Sacco 2019; Sacco 2021; Van Oyen 2016; see Rivers 2016 and Mills 2017 for most recent summaries of different ways network analysis has been used in archaeology). But contrary to other disciplines, where one can observe the connections creating a network while they are still ongoing in the present day, archaeologists need to reconstruct these connections based on material remains, like examining the data from a black box (Brughmans 2010, 282; Knappett 2013, 7–8; Sindbæk 2013, 72, 76). This means that when using network analysis and its algorithms to explore archaeological material, one needs to be aware of issues that can arise from the limitations of the source material.

The first issue is defining the geographic and chronological boundaries of the study. Expanding or contracting these boundaries changes the perspective of the study, as well as its results (Brughmans, Collar, and Coward 2016, 10-2; Knappett 2016, 25-6; Scott 2017, 46–8). Second, the fragmentary nature of the material, part of which is still unexplored, inaccessible, or unstudied and unpublished, even though models have been created to reconstruct missing links (e.g. Tsirogiannis and Tsirogiannis 2016). This creates a risk of bias, which can make some entities (e.g. archaeological sites or types of objects) either over-represented or under-represented in the study only because more or fewer data respectively are available (Brughmans, Collar, and Coward 2016, 10-2; Knappett 2013, 7–8; Knappett 2016, 28-9; Östborn and Gerding 2014, 81–3; see Düring 2016 and Gjesfeld 2015 for examples of how to reduce the bias). Thirdly, the archaeological remains represent points in time, hence diachronically reconstructing the processes that created them can be problematic (Brughmans 2010, 288; Golitko and Feinman 2015, 217; Knappett 2016, 27-8; Mills et al. 2013, 182; Östborn and Gerding 2014, 80–1). Lastly, especially when examining material culture, the classification of objects and the definition of a type are important. What features are considered relevant to differentiate objects? What objects are included in the analysis? Or which ones are excluded and why? Different answers to these questions can lead to different results (Brughmans 2010, 285; Sindbæk 2013, 73).

The described issues will be the topic of the papers included in this session. The papers will present case studies, i.e. applications of network analysis to the study of material culture from any region of the world and any period. These papers will explain how network analysis is applied in archaeology, how the mentioned issues affect the case studies and, most importantly, how the issues are tackled, making it possible to get results and shed light on particular aspects of the past. The issues explored in the session are among the topics regularly explored in the Connected Past conferences, as well as in Knappett 2013 and Brughmans, Anna Collar, and Fiona Coward 2016. However, the mentioned publications and conferences do not focus only on material culture, but explore more ways of applying network analysis, e.g. also to landscapes. On the contrary, the proposed session focuses on artefacts, on how they are collected and classified, on how network analysis is used to examine them, and what research questions can be answered. The aim is to discuss and propose ways of solving issues relevant to when one applies network analysis to archaeological objects.

The issues discussed in the proposed session are already well known in archaeological research that applies network analysis. Attendants of CAA are most probably familiar with them. However, this session gives the opportunity to showcase the most up-to-date research and the latest projects that use network analysis, but which have not yet been presented at the CAA or Connected Past. While younger researchers will have the opportunity to introduce themselves and their research to the community, more experienced researchers will have the opportunity to show the latest advancements in their research, such as new projects or updated results of ongoing projects. The wide chronological and geographical scope of the proposed session will also allow us to include researchers and projects from diverse regions of the world and concerning diverse historical periods. The diverse backgrounds in expertise, historical period, and geographical areas will provide the occasion for networking and fruitful comparisons and discussions, which will help advance the field.

This session will be of interest to different groups of researchers. Firstly, to researchers that are already familiar with, or even experts in, network analysis and want to stay up-to-date, learning about the latest developments in the field. Secondly, to younger researchers that want to make their research known and get in contact with other researchers engaged in the field. Thirdly, to researchers that plan to apply, or are curious about, network analysis and want to learn more about its most recent state. Furthermore, this session aims to demonstrate the potential and usefulness of network analysis in archaeological studies to scholars who may still be sceptical about it, and to introduce this methodology to researchers that are still unaware of it. Lastly, this session will be of use not only to archaeologists, but also to other scholars, such as ancient historians, who are faced with similar problems to most of the ones described.

References

Blake, Emma. 2013. “Social networks, path dependence, and the rise of ethnic groups in pre-Roman Italy.” In Network Analysis in Archaeology, edited by Carl Knappett, 203–22. Oxford: Oxford University Press.

Bolland, John M. 1988. “Sorting out centrality. An analysis of the performance of four centrality models in real and simulated networks.” Social Networks 10: 233–53.

Bonacich, Phillip. 1987. “Power and centrality: a family of measures.” American Journal of Sociology 92 (5): 1170-1182.

Borgatti, Stephen P. 2005. “Centrality and network flow.” Social Networks 27: 55–71.

Brughmans, Tom. 2010. “Connecting the dots: towards archaeological network analysis.” Oxford Journal of Archaeology 29 (3): 277–303.

Brughmans, Tom. 2013. “Thinking through networks: a review of formal network methods in archaeology.” Journal of Archaeological Method and Theory 20 (4): 623–62.

Brughmans, Tom. 2021. “Evaluating the potential of computational modelling for informing debates on Roman economic integration.” In Complexity Economics: Building a New Approach to Ancient Economic History, edited by Koenraad Verboven, 105–23. Cham: Palgrave Macmillan.

Brughmans, Tom, Anna Collar, and Fiona Coward (eds.). 2016. The Connected Past: Challenges to Network Studies in Archaeology and History. Oxford: Oxford University Press.

Brughmans, Tom, Anna Collar, and Fiona Coward. 2016. "Network perspectives on the past: tackling the challenges." In The Connected Past: Challenges to Network Studies in Archaeology and History, edited by Tom Brughmans, Anna Collar, and Fiona Coward, 3–19. Oxford: Oxford University Press.

Carrignon, Simon, Tom Brughmans, and Iza Romanowska. 2020. “Tableware trade in the Roman East: Exploring cultural and economic transmission with agent-based modelling and approximate Bayesian computation.” PLOS ONE 15 (11): e0240414. https://doi.org/10.1371/journal.pone.0240414.

Collar, Anna C.F. 2013. “Re-thinking Jewish ethnicity through social network analysis.” In Network Analysis in Archaeology, edited by Carl Knappett, 223–46. Oxford: Oxford University Press.

Collar, Anna C.F. 2014. “Networks and Ethnogenesis.” In A Companion to Ethnicity in the Ancient Mediterranean, edited by Jeremy McInerney, 97–111. Chichester: Wiley-Blackwell.

Collar, Anna C.F., Fiona Coward, Tom Brughmans, and Barbara J. Mills. 2015. “Networks in archaeology: phenomena, abstraction, representation.” Journal of Archaeological Method and Theory 22 (1): 1–32.

Coward, Fiona. 2010. “Small worlds, material culture and ancient Near Eastern social networks.” Proceedings of the British Academy 158: 453–84.

Coward, Fiona. 2013. “Grounding the net: social networks, material culture and geography in the Epipalaeolithic and Early Neolithic of the Near East (~21,000–6,000 Cal BCE).” In Network Analysis in Archaeology, edited by Carl Knappett, 247–80. Oxford: Oxford University Press.

De Groot, B.G. 2019. “A diachronic study of networks of ceramic assemblage similarity in Neolithic western Anatolia, the Aegean and the Balkans (c.6600–5500 BC).” Archaeometry 61 (3): 600–13.

Düring, Marten. 2016. “How reliable are centrality measures for data collected from fragmentary and heterogeneous historical sources? A case study.” In The Connected Past: Challenges to Network Studies in Archaeology and History, edited by Tom Brughmans, Anna Collar, and Fiona Coward, 85–101. Oxford: Oxford University Press.
Gjesfjeld, Erik. 2015. “Network analysis of archaeological data from hunter-gatherers: methodological problems and potential solutions.” Journal of Archaeological Method and Theory 22 (1): 182–205.

Golitko, Mark, and Gary M. Feinman. 2015. “Procurement and distribution of pre-Hispanic Mesoamerican obsidian 900 BC–AD 1520: a social network analysis.” Journal of Archaeological Method and Theory 22 (1): 206–47.

Knappett, Carl. 2011. An Archaeology of Interaction: Network Perspectives on Material Culture and Society. Oxford: Oxford University Press.

Knappett, Carl (ed.). 2013. Network Analysis in Archaeology. Oxford: Oxford University Press.

Knappett, Carl. 2013. “Introduction: why networks?” In Network Analysis in Archaeology, edited by Carl Knappett, 3–16. Oxford: Oxford University Press.

Knappett, Carl. 2016. “Networks in archaeology: between scientific method and humanistic metaphor.” In The Connected Past: Challenges to Network Studies in Archaeology and History, edited by Tom Brughmans, Anna Collar, and Fiona Coward, 21–33. Oxford: Oxford University Press.

Linton C. Freeman. 1979. “Centrality in social networks. Conceptual clarification.” Social Networks 1: 215–39.

Mills, Barbara J. 2017. “Social Network Analysis in Archaeology.” Annual Review of Anthropology 46: 379–97.

Mills, Barbara J., John M. Roberts Jr., Jeffery J. Clark, William R. Haas Jr., Deborah L. Huntley, Matthew A. Peeples, Lewis Borck, Susan C. Ryan, Meaghan Trowbridge, and Ronald L. Breiger. 2013. “The dynamics of social networks in the late prehispanic US Southwest.” In Network Analysis in Archaeology, edited by Carl Knappett, 181–202. Oxford: Oxford University Press.

Östborn, Per, and Henrik Gerding. 2014. “Network analysis of archaeological data: a systematic approach.” Journal of Archaeological Science 46: 75–88.

Östborn, Per, and Henrik Gerding. 2015. “The diffusion of fired bricks in Hellenistic Europe: a similarity network analysis.” Journal of Archaeological Method and Theory 22 (1): 306–44.

Peeples, Matthew A., Barbara J. Mills, W. Randall Haas, Jeffery J. Clark, and John M. Roberts Jr. 2016. “Analytical challenges for the application of social network analysis in archaeology.” In The Connected Past: Challenges to Network Studies in Archaeology and History, edited by Tom Brughmans, Anna Collar, and Fiona Coward, 59–84. Oxford: Oxford University Press.

Rawat, Nagendra Singh, Tom Brughmans, Vinod Nautiyal, and Devi Dutt Chauniyal. 2021. “Networked Medieval strongholds in Garhwal Himalaya, India.” Antiquity 95 (381): 753–72.

Rivers, Ray. 2016. “Can Archaeological Models Always Fulfil our Prejudices?” In The Connected Past: Challenges to Network Studies in Archaeology and History, edited by Tom Brughmans, Anna Collar, and Fiona Coward, 123–47. Oxford: Oxford University Press.

Sacco, Arianna. 2019. “Game of Dots: Using Network Analysis to Examine the Regionalization in the Second Intermediate Period.” In The Enigma of the Hyksos. Volume I, edited by Manfred Bietak and Silvia Prell, 369–96. Wiesbaden: Harrassowitz Verlag.

Sacco, Arianna. 2021. “More Than People and Pots: Identity and Regionalization in Ancient Egypt, ca 1775-1550 BC”, PhD thesis defended at Leiden University.

Scott, John. 2017. Social Network Analysis. 4th ed. London: SAGE.

Sindbæk, Søren Michael. 2007. “The small world of the Vikings: networks in early Medieval communication and exchange.” Norwegian Archaeological Review 40 (1): 59–74.

Sindbæk, Søren Michael. 2013. “Broken links and black boxes: material affiliations and contextual network synthesis in the Viking world.” In Network Analysis in Archaeology, edited by Carl Knappett, 71–94. Oxford: Oxford University Press.

Terrell, John Edward. 2010. “Language and material culture on the Sepik coast of Papua New Guinea: using social network analysis to simulate, graph, identify, and analyze social and cultural boundaries between communities.” Journal of Island & Coastal Archaeology 5 (1): 3–32.

Tsirogiannis, Constantinos and Christos Tsirogiannis. 2016. “Uncovering the hidden routes: algorithms for identifying paths and missing links in trade networks.” In The Connected Past: Challenges to Network Studies in Archaeology and History, edited by Tom Brughmans, Anna Collar, and Fiona Coward, 103-20. Oxford: Oxford University Press.

Van Oyen, Astrid. 2016. “Networks or work-nets? Actor-Network Theory and multiple social topologies in the production of Roman Terra Sigillata.” In The Connected Past: Challenges to Network Studies in Archaeology and History, edited by Tom Brughmans, Anna Collar, and Fiona Coward, 35–56. Oxford: Oxford University Press.

S09: Archaeology and digital humanities: the road already travelled and the road ahead (Roundtable)

Christophe Tuffery, INRAP

Leticia Tobalina-Pulido, Casa de Velázquez-EHEHI

Cesar Gonzalez-Perez, Incipit (Institute of Heritage Sciences) of the CSIC (Spanish National Research Council)

Background information on the theme and a brief summary of past developments

It is admitted that archaeology and archaeologists are very often absent from debates, conferences, papers about digital humanities. Most of archaeologists do not know exactly what digital humanities are consisting in and a few of them identify themselves as digital humanists. Their research projects are rarely funded from the agencies and programs concerning digital humanities. Ethan Watrall proposed to see digital humanities as a metaphor of a tent (Watrall 2016). As this author wrote, “most archaeologists (…) are so far away from the tent that they cannot even see it”. This session proposes to give an opportunity for archaeologists to make the point on this lack and to identify ways of reinforce the place of archaeologists in digital humanities debates and practices.

With the development and a large use of ITC, archaeologists reached a new step in the evolution of their tools and methods available for producing archaeological observations and documentation as well. Archaeology is “moving to an age of data-centric, data-driven analysis or data-led thinking, in which data takes pre-eminence over theory” (Huggett 2020). Astonishing, these new conditions of production of archaeological knowledge are rarely put in questions from an epistemological point of view. This lack shed lights on the fact that it becomes necessary to develop a more reflexive about building digital archaeological knowledge and their impacts to archaeological reasoning.

A snapshot of current research in the field and the directions in which it is heading

For less than a decade, some archaeologists, involved is use of several digital tools and methods, began to enlarge their own communities and discussions to those of other disciplines such as geography, history, philology, epigraphy, archive studies, etc.
Archaeologists began to use digital technologies and tools such as DBMS in 1980s, then mapping software and GIS in 1990s, and GPS and digital photo and satellite imageries in 2000s. In the last decade, new data such as Lidar or high-resolution photos from drones or other sensors, were included in the toolbox of tools and methods used by archaeologists, such as photogrammetry, geophysics, and computed tomography were widely developed to address needs of data acquisition and treatment. Some experiments were also engaged in the use artificial intelligence to explore massive archaeological sets of big data (Djindjian 2020) as well as virtual or immersive reality (Quinio and al. 2020 ) to present archaeological remains and sites, mainly for public exhibits : Pompei (http://pompeii.refutur.com/en/), Syria (http://syrianheritagerevival.org/), etc., more rarely for research projects such as SCHOPPER project (http://schopper-anr.org/). The importance and potential contributions of research in the field :
They could identify researchers from other disciplines of digital humanities so that they could engage collaborations with crossed benefits.

Archaeologists have probably to better identify and address challenges and problems in using some of digital technologies without reinventing the wheel, so that they could reach a new step in their digital practices according to scientific problems and requirements of scientificity.

One major issue is to improve capacities of archaeologists to know how to be involved in transdisciplinary projects and not only in multidisciplinary ones. Research activities to be engaged in this domain would have as objective for archaeologists not to become computer specialists but to know where to find digital skills they could need and to be able to collaborate with them. Another objective for archaeologists could be to identify trends and capacities of digital technologies already used in other disciplines that could be adapted in their own.

Officials form archaeology organisations (EAA, etc.) could define prospective reflexions for next decades in the aim to give orientations and major issues to be achieved in the context of main research and funding programs at a European (H2020, etc.) and worldwide levels.

Examples of prospective content for paper

  • What kind of scientific and/or technical “revolution” does digital tools and methods are representing for archaeology
  • What are the conditions for archaeologists to use tools and methods of digital humanities according to scientific needs?
  • How archaeologists may compare their methods and results to other disciplines and domains of expertise, which are using the same tools and methods?
  • How archaeologists may better be involved in transdisciplinary projects in digital humanities?
  • Are archaeologists enough trained and well informed to know all digital technologies available in their domains of research?
  • What could be the modifications in teaching programs that digital humanities could invite academic institutions in the archaeology domain?
  • What about the role of computer scientists in the projects of digital humanities involving archaeologists?
  • How could it be possible to promote theoretical discussions about the use of new technologies in archaeology?

Likely audiences for your proposed session

  • archaeologists
  • specialists in digital archaeology and digital humanities
  • computer scientists
  • officials from organizations in archaeology
  • organizations in other disciplines involved in digital humanities

All these technologies are used by archaeologists within the various stages of the research data life cycle, that may be ordered in three main steps: preparation (prospect: desk research and exploratory field research), data collection (excavation) and data analysis (descriptive and analytic research).

References

Ethan Watrall (2016). “Archaeology, the Digital Humanities, and the “Big Tent”“ in Debates in the Digital Humanities 2016. Published by: University of Minnesota Press. URL: https://www.jstor.org/stable/10.5749/j.ctt1cn6thb.31

François Djindjian (2020). “Big data and archaeology”. In Big data and singularities. Creativity as a Basis for Rethinking the Human Condition. Humanities Arts and Societies Magazine pp. 208-217 http://humanitiesartsandsociety.org/wp-content/uploads/2020/07/HAS-Magazine-01-Big-Data-and-Singularities-EN.pdf

Jeremy Huggett (2020). “Is Big Digital Data Different? Towards a New Archaeological Paradigm”, Journal of Field Archaeology, 45:sup1, S8-S17, DOI: 10.1080/00934690.2020.1713281

Quinio B., Boulbes N., De Pechpeyrou P., Kotras B. (2020). ”Use cases of virtual reality to visualize a database: how useful is VR for archaeology researchers?” Digital Tools & Uses Congress (DTUC’20), October 15–17, 2020, Hammamet, Tunisia. ACM, New York, NY, USA, 8p. http://www.digitaluses-congress.univ-paris8.fr/Data-and-Digital-Humanities

S10: Digital Archaeology in the Gulf: New solutions to old problems (Standard)

Jennifer Swerida, Penn Museum, University of Pennsylvania

Eli Dollarhide, New York University Abu Dhabi

Selin Nugent, Oxford Brooks University

Robert Bryant, University of Pennsylvania

The archaeology of the Gulf Region of the Middle East presents unique challenges to researchers in the 21st century. This area, including Arabia, southern Mesopotamia and Iran, and the Indus Valley, is home to some of the world’s first cities, states, and most iconic archaeological sites. This situation has made the Gulf backdrop to the development of many traditional fieldwork methods, including broad-scale landscape survey (Braidwood et al. 1983), settlement pattern analysis (Adams 1965), and the use of aerial photography (Kennedy and Bewley 2004; Stone 1991). In the years since these foundational achievements, geopolitical challenges and deteriorating environmental conditions have resulted in inconsistent access to on-the-ground research and limited the implementation of some digital archaeological approaches common to other regions. This disjointed development has resulted in uneven states of the field and limited interactions between scholars working in these different countries.

This session addresses these challenges by inviting scholars working throughout this region into conversation with each other about these challenges and the strategies they have developed to overcome them. The papers presented here will bring traditionally divergent groups of regional specialists together. Potential topics include the use of geophysical prospection (Herrmann 2013; Khan et al. 2021), drone-based survey and mapping (Smith 2020), applications of satellite imagery (Harrower 2013; Sivitskis et al. 2018; Ur 2013), digital approaches to preservation and conservation management (Rayne and Bewley 2016; Zerbini 2018), agent-based modeling (Angourakis et al. 2020), and the application of artificial intelligence (Orengo et al. 2020; Nugent in prep) in contexts across the Middle East. Audience members may include researchers with active field projects in Gulf states, digital archaeological innovators, and the heritage community of the greater Middle East.

References

Adams, R.M., 1965. Land Behind Baghdad: A history of settlement on the Diyala Plains. University of Chicago Press, Chicago.

Angourakis, A. et al., 2020. How to ‘Downsize’ a Complex Society: An agent-based modeling approach to assess the resilience of Indus Civilization settlements to past climate change. Environment Research Letters 15(11): 115004.

Braidwood, L.S., 1983. Prehistoric Archaeology along the Zagros Flanks. University of Chicago Press, Chicago.

Harrower, M.J., 2013. Methods, Concepts, and Challenges in Archaeological Site Detection and Modeling. In D.C. Comer and M.J.

Harrower (eds.) Mapping Archaeological Landscapes from Space, 213-218. Springer, New York.

Herrmann, J.T. , 2013. Three-Dimensional Mapping of Archaeological and Sedimentary Deposits with Ground-penetrating Radar at Saruq al-Hadid, Dubai, United Arab Emirates. Archaeological Prospection 20(3): 189-203. Doi: 10.1002/arp.1456.

Kennedy, D.L. and R. Bewley., 2004. Ancient Jordan from the Air. The British Academy: Council for British Research in the Levant.

Khan, N. et al., 2021. Integrated Geophysical Study of Lower Indus Basin at Regional Scale. Arabian Journal of Geosciences 14, 1214. Do: 10.1007/s12517-021-07568-4.

Orengo, H.A. et al., 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.

Nugent, S., in prep. AI Monitoring of Erosion and Threat to Archaeological Sites in Southeast Arabia.

Rayne, L. and R. Bewley., 2016. Using Satellite Imagery to Record Endangered Archaeology. Remote Sensing and Photogrammetry Society Archaeology Special Interest Group Newsletter. September 2016: 15-20.

Sivitskis, A.J. et al., 2018. Hyperspectral Satellite Imagery Detection of Ancient Raw Material Sources: Soft-stone vessel production at Aqir al-Shamoos (Oman). Archaeological Prospection 25(4): 363-374. Doi: 10.1002/arp.1719.

Smith, S.L., 2020. Drones over the “Black Desert”: The Advantages of Rotary-Wing AUVs for Complementing Archaeological Fieldwork in Hard-to-Access Landscapes of Preservation of North-Eastern Jordan. Geosciences 2020, 10, 426. Doi: 10.3390/geosciences10110426.

Stone, E., 1991. The Spatial Organization of Mesopotamian Cities. Aula Orientalis 9: 235-242.

Ur, J.A., 2013. Spying on the Past: Declassified intelligence satellite photographs and near eastern landscapes. Near Eastern Archaeology 76(1): 28-36.

Zerbini, A., 2018. Developing a Heritage Database for the Middle East and North Africa. Journal of Field Archaeology 45(1): 9-18. Doi 10.1080/00934690.2018.1514772.

S11: Mountains of Data. Digital Mountain Archaeology in Global Perspective (Standard)

Cinzia Bettineschi, University of Augsburg (Germany)

Luigi Magnini, Department of History, Human Sciences and Education, University of Sassari (Italy)

According to the United Nations Environment Programme – World Conservation Monitoring Centre, mountains cover more than one quarter of the Earth’s land surface (Rodríguez-Rodríguez et al., 2011). The fragility of these ecosystems and their exceptional historic-archaeological potential are constantly threatened by natural hazards, human-induced climate changes (Fort, 2015), and by an increasing loss of biocultural diversity (Agnoletti & Rotherham, 2015).

On one side, modern socio-economic pressure is causing the abandonment of wide mountainous areas, their pastures, and of long-established forest management systems, which are seldom replaced by adequate monitoring strategies (Dax et al., 2021). On the other, mass tourism and the economical attractivity of mountain resources are leading to an uncontrolled exploitation of the local environment (Taczanowska et al., 2019), increasing the risk of destruction both for traditional landscapes and archaeological remains.

Despite the enormous variability in mountain environments, archaeologists working in such contexts have to face specific challenges, including – as applicable – dense afforestation, inaccessibility, significant erosion, altitude and temperature-related technical issues which require proactive mitigation and contingency measures (Carrer et al., 2020; Caspari, 2021; Pelisiak et al., 2018).

In this framework, the opportunities offered by digital methods constitute a fundamental help for contributing to a sustainable identification, documentation, monitoring, and management of the montane cultural record (Brogiolo et al., 2012). The recent advances in hardware solutions, and sensor typology, resolution, and portability are constantly improving the potential of remote/ near sensing and 3D modeling for earth observation and field prospection of mountainous areas (Lambers, 2018; Reinhold et al., 2016; Stek, 2016). Artificial intelligence is further pushing the computational power of such approaches, offering an efficient system to process huge amounts of data in relatively short timeframes (Chen et al., 2021; Magnini et al., 2017; Sărășan et al., 2020). Furthermore, the development of dedicated predictive models using advanced spatial methods and ontological reasoning is contributing to identify and protect endangered archaeological contexts (Magnini & Bettineschi, 2021; Märker & Heydari-Guran, 2010; Stirn, 2014; Visentin & Carrer, 2017).

This session constitutes an opportunity to disseminate the most promising results of the digital heritage community in the field of mountain archaeology and welcomes case studies, methodological developments, and position papers. The main topics can include (but are not limited to):

  • Aerial and satellite remote sensing from local to global scale, including advanced image enhancing & data processing techniques, and spatial analyses for site detection and settlement pattern identification;
  • UAVs and other autonomous vehicles in extreme mountain environments;
  • Predictive and Agent-based modeling for the spatio-temporal modeling of human/ landscape interactions;
  • Artificial Intelligence (broadly defined) and big data;
  • Digital methods for risk management, heritage protection, land use/ land cover/ land change assessment;
  • 3D modeling for the documentation and communication of mountain cultural heritage, including design of Augmented/ Virtual, and Enhanced Reality experiences.

References

Agnoletti, M., & Rotherham, I. D. (2015). Landscape and biocultural diversity. Biodiversity and Conservation, 24(13), 3155–3165. https://doi.org/10.1007/s10531-015-1003-8

Brogiolo, G. P., Angelucci, D. E., Colecchia, A., & Remondino, F. (Eds.). (2012). APSAT 1: teoria e metodi della ricerca sui paesaggi d’altura. SAP.

Carrer, F., Walsh, K., & Mocci, F. (2020). Ecology, Economy, and Upland Landscapes: Socio-Ecological Dynamics in the Alps during the Transition to Modernity. Human Ecology, 48(1), 69–84. https://doi.org/10.1007/s10745-020-00130-y

Caspari, G. (2021). Tracking the Cold: Remote Sensing for Glacial Archaeology. Journal of Glacial Archaeology, 5, 85–102. https://doi.org/https://doi.org/10.1558/jga.19823

Chen, F., Zhou, R., Van de Voorde, T., Chen, X., Bourgeois, J., Gheyle, W., Goossens, R., Yang, J., & Xu, W. (2021). Automatic detection of burial mounds (kurgans) in the Altai Mountains. ISPRS Journal of Photogrammetry and Remote Sensing, 177, 217–237. https://doi.org/10.1016/j.isprsjprs.2021.05.010

Dax, T., Schroll, K., Machold, I., Derszniak-Noirjean, M., Schuh, B., & Gaupp-Berghausen, M. (2021). Land Abandonment in Mountain Areas of the EU: An Inevitable Side Effect of Farming Modernization and Neglected Threat to Sustainable Land Use. Land, 10(6), 591. https://doi.org/10.3390/land10060591

Fort, M. (2015). Impact of climate change on mountain environment dynamics. Revue de Géographie Alpine, 103–2. https://doi.org/10.4000/rga.2877

Lambers, K. (2018). Airborne and Spaceborne Remote Sensing and Digital Image Analysis in Archaeology (pp. 109–122). https://doi.org/10.1007/978-3-319-25316-9_7

Magnini, L., & Bettineschi, C. (2021). Object-Based Predictive Modeling (OBPM) for Archaeology: Finding Control Places in Mountainous Environments. Remote Sensing, 13(6), 1197. https://doi.org/10.3390/rs13061197

Magnini, L., Bettineschi, C., & De Guio, A. (2017). Object-based Shell Craters Classification from LiDAR-derived Sky-view Factor. Archaeological Prospection, 24(3), 211–223. https://doi.org/10.1002/arp.1565

Märker, M., & Heydari-Guran, S. (2010). Application of datamining technologies to predict Paleolithic site locations in the Zagros Mountains of Iran. In B. Frischer, J. Webb Crawford, & D. Koller (Eds.), Proceedings of Computer Applications in Archaeology, March 22–26, 2009 (pp. 1–7). BAR International Series.

Pelisiak, A., Nowak, M., & Astalos, C. (Eds.). (2018). People in the mountains: current approaches to the archaeology of mountainous landscapes. Archaeopress.

Reinhold, S., Belinskiy, A., & Korobov, D. (2016). Caucasia top-down: Remote sensing data for survey in a high altitude mountain landscape. Quaternary International, 402, 46–60. https://doi.org/10.1016/j.quaint.2015.10.106

Rodríguez-Rodríguez, D., Bomhard, B., Butchart, S. H. M., & Foster, M. N. (2011). Progress towards international targets for protected area coverage in mountains: A multi-scale assessment. Biological Conservation, 144(12), 2978–2983. https://doi.org/10.1016/j.biocon.2011.08.023

Sărășan, A., Ardelean, A.-C., Bălărie, A., Wehrheim, R., Tabaldiev, K., & Akmatov, K. (2020). Mapping burial mounds based on UAV-derived data in the Suusamyr Plateau, Kyrgyzstan. Journal of Archaeological Science, 123, 105251. https://doi.org/10.1016/j.jas.2020.105251

Stek, T. D. (2016). Drones over Mediterranean landscapes. The potential of small UAV’s (drones) for site detection and heritage management in archaeological survey projects: A case study from Le Pianelle in the Tappino Valley, Molise (Italy). Journal of Cultural Heritage, 22, 1066–1071. https://doi.org/10.1016/j.culher.2016.06.006

Stirn, M. (2014). Modeling site location patterns amongst late-prehistoric villages in the Wind River Range, Wyoming. Journal of Archaeological Science, 41, 523–532. https://doi.org/10.1016/j.jas.2013.09.018

S12: Formal modelling and models of social complexity - in concepts, numbers, equations and agents (Standard)

Iza Romanowska, Aarhus Insitute of Advanced Studies, Aarhus University, Denmark

Claudio Cioffi-Revilla, George Mason University, USA

CAA has a historically long tradition fostering formal theory and research on social complexity, building on earlier foundations by social scientists (including archaeologists), mathematicians, and computer scientists. These approaches proliferated in archaeology as they helped researchers to understand past societies, their evolution, transformations and strategies in new and exciting ways. This stands in contrast to the rapid empirical shift whereby researchers increasingly invest in data-intensive approaches and digital means of analysing them. As a result, we are seeing a significant rise in robust and more mature scientific practices in archaeology for examining past peoples and their polities in a systematic, formal, testable, and reproducible way.

Modelling links data and, in particular, trends in data to causal processes (whether social, natural, cultural, etc) that gave rise to them. While data analysis answers such questions as “what?”,”where?”, “when?” or “how many?”, modelling focuses on “why?” and “how?” making the two approaches complementary and in many cases necessary if the goal is to understand long-term trajectories of human groups.

This session is dedicated to archaeological models of all types: conceptual, mathematical, or computational. To stimulate a discussion on the role of models and modelling in archaeology we hope to encourage wider use of formal methodologies, in particular, computational models. The goals of this session are:

  • To showcase the best applications of different forms of formal modelling to archaeological questions concerned with social complexity. This can include but is not limited to agent-based models, mathematical models, spatial and statistical models, formal ontologies etc.
  • To exchange new and exciting avenues of research such as new modelling methods, surprising applications of models from other disciplines, or new techniques and tools that other modellers should be aware of.
  • To discuss the “academic outreach” of the modelling community and explore innovative ways of teaching, presenting, and using formal models in and outside of the world of academia.

While the format of the session calls for standard 20-minute presentations we will happily consider alternative formats, such as software demos, coordinated discussions over pilot studies or even interpretative dance. We will encourage participants to share publications, drafts, data, and code prior to the event so that participants can engage in a more informed and meaningful exchange at the conference venue.

Papers addressing the following themes and other investigations of social complexity origins and pre-modern phases are sought for this session:

1. Formal models of social complexity, whether computational or mathematical
a) Agent-based models of the emergence of social complexity (With or without geospatial landscapes)
b) Mathematical models of social complexity formative phases

2. Computational or mathematical tools for analysis of long-term patterns of social complexity
a) Braudelian long-duree
b) Cycling patterns of social complexity
c) Long-range geospatial analysis of social complexity
d) Spatiotemporal hyperspatial models of social complexity

3. Formal conceptual analysis of social complexity
a) Use of computational tools such as UML, SysML, and other formalism for conceptual analysis
b) Network-theoretic models of social complexity
c) Comparative conceptual analysis of social complexity using formal methods

4. Formative phases of social complexity

5. Social complexity in comparative perspective: cross-polity analysis

6. Data sonification for social complexity

S13: Machine and deep learning methods in archaeological research: beyond site detection (Standard)

Arnau Garcia-Molsosa, Catalan Institute of Classical Archaeology

Hector A. Orengo, Catalan Institute of Classical Archaeology

Iban Berganzo-Besga, Catalan Institute of Classical Archaeology

Although machine learning (ML) and deep learning (DL) related methods have been in use for several decades, they have only been applied to archaeological problems recently. Some early implementations focussed on the classification, seriation and analysis of material culture such as artistic representations (Barceló 1995a and 1995b, Di Ludovico and Ramazzotti 2005), use-wear of prehistoric tools (Van den Dries 1998), historical glass artifacts and ancient coins (Van der Maaten et al. 2007). The application of ML and DL in archaeology has experienced a strong turn towards the detection of archaeological sites during the last years (but see Wright and Gattiglia 2018 and Orengo and Garcia-Molsosa 2019 for the identification of ceramic fragments and Oonk and Spijker 2015 for geochemical analysis) making heavy use of multispectral satellite and lidar data. Since the pioneering work of Menze and Ur 2012, the wider availability of data (in particular high-resolution lidar), cloud computing platforms and AI processes and code has boosted ML and DL site-based detection (e.g. Lisset al. 2017, Trier et al. 2018, Berganzo-Besga et al. 2021).

Despite the importance of site location for the discipline, it is obvious that ML and DL enclose enormous potential to boost many areas of archaeological research, particularly within but not restricted to the field of computer vision. ML and DL are able to build inference models from sample data that can organise information without the need to explicitly program the process. Archaeologists are gaining skills and access to computational resources while, at the same time, new interfaces facilitate the use of these techniques to researchers not specialised in computer methods (see, e.g. Altaweel et al. 2022). The increased availability of models and examples opens the possibility to extend the debate towards how specific historical and archaeological debates can benefit from these new analytical instruments and the knowledge they generate.

This session aims to bring together archaeological ML and DL applications, discuss the problems related to their application and offer insight on to best practices. We welcome contributions about the application of ML and DL to different aspects of archaeological research and practice. With that perspective, we expect to provide a platform where the participants can observe and discuss the ensemble of opportunities that ML and DL can provide, with special interest on the possibility to create synergies between different fields of application, that are being developed in isolation.

Some of the suggested topics for the session are:

  • Case studies on the application of AI to different sources of archaeological information. That can include the analysis of texts, artistic representations, bioarchaeological remains, material culture or archaeological sites. Combinations of such will be particularly welcome.
  • Best practices and procedures, which can include comparative analysis. We are interest on examples on how to approach sensible datasets and how to facilitate reproducibility and Open Science principles in general.
  • Big-data, data cleaning, data augmentation and data ingestion, as transversal challenges in many fields. Contributions addressing how researchers are developing, working with and taking advantage of large datasets, problems arising and potential solutions.
  • The continuously increasing availability of detectors and methods makes sometimes difficult to select the best processes and algorithms for specific tasks. In this regard we welcome talks on algorithm selection, modification and performance evaluation.
  • Talks addressing the development of computationally cost-effective workflows, in particular for the use or analysis of large datasets and the application of intensive computing processes will constitute a welcome addition to the session’s discussion.

References

Altaweel M, Khelifi A, Li Z, Squitieri A, Basmaji T, Ghazal M. Automated Archaeological Feature Detection Using Deep Learning on Optical UAV Imagery: Preliminary Results. Remote Sensing. 2022; 14(3):553. https://doi.org/10.3390/rs14030553

Barceló, J.A. 1995a. Back-propagation algorithms to compute similarity relationships among archaeological artifacts. In J. Wilcock & K. Lockyear (Eds.), Computer applications in archaeology (pp. 165-176). Oxford: ArcheoPress. (British Archaeological Reports S598).

Barceló, J.A. 1995b. Seriación de Datos Arqueológicos Ambigüos o Incompletos. Una Aplicacion de las Redes Neuronales. In Aplicaciones Informáticas en Arqueología. Teoría y Sistemas (vol. II.) (pp. 99-116) Bilbao (Spain): Denboraren Argia.

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, 13(20), p. 4181

Di Ludovico, A., & Ramazzotti, M. 2005. Reconstructing lexicography in glyptic art: Structural relations between the Akkadian Age and the Ur III period. In LI Rencontre Assyriologique Internationale. Retrieved October 2007 from http://www.let.leidenuniv.nl/rencontre/RAI_2005/RAI_2005.html

Orengo, H. A., & Garcia-Molsosa, A. (2019). A brave new world for archaeological survey: Automated machine learning-based potsherd detection using high-resolution drone imagery. Journal of Archaeological Science, 112, 105013. https://doi.org/10.1016/j.jas.2019.105013

Liss, B.; Howland, M.D. & Levy, T.E. 2017. Testing Google Earth Engine for the automatic identification and vectorization of archaeological features: A case study from Faynan, Jordan. Journal of Archaeological Science: Reports, 15: 299-304.

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.

Oonk, S. & Spijker, J. 2015. A supervised machine-learning approach towards geochemical predictive modelling in archaeology. Journal of Archaeological Science, 59: 80-88.

Trier, Ø.D., Cowley, D.C. & Waldeland, A.U. 2018. Using deep neural networks on airborne laser scanning data: Results from a case study of semi‐automatic mapping of archaeological topography on Arran, Scotland. Archaeological Prospection. https://doi.org/10.1002/arp.1731

Van den DRIES, M.H. 1998. Archeology and the application of artificial intelligence. Case studies on use-wear analysis of prehistoric flint tools. Archaeological Studies Leiden University No. 1., Faculty of Archaeology, University of Leiden (Holland).

Van der Maaten, L.J.P.; Boon, P.J.; Paijmans, J.J.; Lange, A.G. & Postma, E.O. 2007. Computer Vision and Machine Learning for Archaeology. In J.T. Clark and M. Hagemeister (eds.) Digital Discovery. Exploring New Frontiers in Human Heritage. Computer Applications and Quantitative Methods in Archaeology. Archaeolingua, Budapest.

Wright, H. & Gattiglia, G. 2018. ArchAIDE: Archaeological Automatic Interpretation and Documentation of ceramics, Proceedings of the Workshop on Cultural Informatics Research and Applicationsco-located with the International Conference on Digital Heritage, Nicosia, Cyprus, November 3, 2018. 60-65.

S14: Large-scale and intensive computational workflows in archaeological remote sensing: from big data to data science (Standard)

Francesc C. Conesa, Catalan Institute of Classical Archaeology

Arnau Garcia-Molsosa, Catalan Institute of Classical Archaeology

Hector A. Orengo, Catalan Institute of Classical Archaeology

The last few years have seen an unprecedented advance in the application of computational approaches for the remote analysis of archaeological landscapes, sites and features. This progress is mostly related to improvements in availability, diversity and quality of remote sensing data acquired from multiple platforms (ranging from satellite imagery to UAVs) and sensors (e.g. multispectral, radar, lidar, thermal) but also to increased access to high performance computing. This is partly related to the development of multi-petabyte catalogues of geospatial datasets linked to cloud computing environments accessible through web-based application programming interfaces associated to interactive development environments. These have granted the research community unparalleled access to geospatial data and computing power, and facilitated the development of large-scale, multi-temporal and multi-sensor analyses of the Earth’s surface. These environments have also been instrumental in the implementation of intensive computational processes, such as machine learning-based data classification, multi-scale topographic analysis, long-term time series analysis, and so on.
Many computing platforms have recently gain some popularity and are boosting a fast-growing number of applications. Among those, we highlight the of Amazon Web Services or the Data and Information Access Services that are run by the Copernicus satellite program. In particular, Google’s Earth Engine have been integrated into the archaeologist toolkit in a wide range of topics such as site detection and the long-term monitoring and management of cultural landscapes (see for instance Agapiou 2016; Rayne e al. 2017; Orengo and Petrie, 2018; Orengo 2020, Agapiou 2021).

This session will aim at showcasing and discussing new computational workflows for the treatment and analysis of large or complex remote sensing and other geospatial datasets. The adoption of cloud-computing platforms and other reproducible processing operations ultimately leave more time and resources for data interpretation and compared studies. We therefore encourage submissions that highlight innovative remote-based archaeological applications in the following or similar topics:

  • Implementation of high-performance computing workflows
  • Application of cloud-based computing platforms to archaeological remote sensing problems
  • Use of multi-petabyte repositories of geospatial datasets
  • Complex computing or multiplatform workflows
  • Remote sensing analysis of large areas
  • Landscape analyses over time-series
  • Geospatial data cleaning and preparation
  • Synergistic use of multispectral and radar satellite imagery
  • Integration of multi-sensor or complex types of remote sensing data

References

Agapiou, A. (2017). Remote sensing heritage in a petabyte-scale: satellite data and heritage Earth Engine© applications. Int. J. Digit. Earth 10: 85–102.

Agapiou, A. (2021). Multi-Temporal Change Detection Analysis of Vertical Sprawl over Limassol City Centre and Amathus Archaeological Site in Cyprus during 2015–2020 Using the Sentinel-1 Sensor and the Google Earth Engine Platform. Sensors, 21

Garcia, A., Orengo, H., Conesa, F., Green, A. and Petrie, C. (2018). Remote Sensing and Historical Morphodynamics of Alluvial Plains. The 1909 Indus Flood and the City of Dera Gazhi Khan (Province of Punjab, Pakistan). Geosciences 9: 21.

Orengo, H. A. and Petrie, C. A. (2018). Multi-scale relief model (MSRM): a new algorithm for the visualization of subtle topographic change of variable size in digital elevation models. Earth Surf. Process. Landforms 43: 1361-1369.

Orengo, H. A. and Garcia, A. (2019, in press). A brave new world for archaeological survey : automated machine learning-based potsherd detection using high-resolution drone imagery. J. Archaeol. Sci.

Rayne, L., Bradbury, J., Mattingly, D., Philip, G., Bewley, R. and Wilson, A. (2017). From Above and on the Ground: Geospatial Methods for Recording Endangered Archaeology in the Middle East and North Africa. Geosciences 7: 100

S15: Workflows and experiences on collaborative working and community building using digital tools (Other)

Martin Hinz, University of Bern

Florian Thiery, Römisch-Germanisches Zentralmuseum, Mainz, Germany

Sophie C. Schmidt, Free University Berlin, Germany

For a long time now, archaeological research has not been conducted by individual researchers who come up with brilliant theories in their study rooms and investigate them by themselves and on their own terms. It is a fact that no serious scientific research can be conducted without substantial and extensive collaboration.

The internet facilitated a significant change in work processes, something we have been able to experience vividly in the last two years. Since it was intended from the start as a tool to enable scientific exchange, it is all the more astonishing that collaborative work via the internet did not develop further from back-and-forth emailing of text manuscripts for such a long time. By now there are a variety of different systems and solutions: communication via Slack or Signal, co-writing via Google Docs or Overleaf, data co-creation in online database systems, Open Science Framework or Wikidata, as well as code co-development via GitHub or GitLab.

Streamlined and meaningful collaborative work on research questions is possible nowadays, not just with textual products. Especially in the case of analytical archaeology, where data analysis is a focal point, scientific scripting languages shine. There are several research tools and little minions that combine textuality with machine executability to facilitate a collaborative process of thought and analysis.

In recent years, we think, version controlled workflows, e.g. GIT-based, have become established in this field. But that is certainly not all, as there are a multitude of different solutions to this challenge! Quite often the difficulty lies in finding the best work-flow for certain people or groups. For this reason, in this session we would like to bring together those who work on collective projects, shared software development, reproducible research as well as collaborative writing and data acquisition based on different platforms, and let us and a broad community of researchers in on their workflows.

We invite you to address, but not be limited to, the following questions in a short lightning talk (max. 7 mins):

  • Which technologies and workflows have proven effective, which are dead ends?
  • How did you generate the Community? And did you keep the ball rolling to create a sustainable structure of collaboration?
  • How can you make the best use of the possibilities of collaborative writing and analysis with the help of interlinked workplaces?
  • Which tools and approaches are suitable for keeping a scattered team together and motivating it?
  • What limits and problems arise in connection with the joint development of reproducible script-based analyses?
  • How did you overcome challenges you faced when switching to a digital workflow?

After the presentations an open discussion led by the session chairs is intended to stimulate a further exchange of workflows. Both, this session and a workshop on scientific co-creation using Git and Github are organised by the CAA Special Interest Group for Scientific Scripting Languages in Archaeology in cooperation with the CAA SIG on Semantics and LOUD in Archaeology (Data-Dragon).

S16: Reaching across the digital divide: towards equitable practice in digital archaeology and heritage management (Roundtable)

Rebecca Roberts, University of Cambridge

Faye Lander - University of the Witwatersrand

Stefania Merlo, University of Cambridge

Azadeh Vafadari, University of Cambridge

Cameron Petrie, University of Cambridge

Paul Lane, University of Cambridge

Bonnie Etter, Southern Methodist University

Abigail Fisher, Southern Methodist University

The digital divide is far from a new phenomenon. In the last three decades global intergovernmental bodies with large-scale initiatives including the International Telecommunications Union (ITU), the United Nations World Summit on the Information Society (WSIS 2021), as well as UNESCO’s Fostering Innovation and Inclusive Digital Transformation for Sustainable Development Programme (Anon 2021) (2021), to name a few, have raised the alarm about the disparities in digital access, digital affordability, digital knowledge production, and fundamental digital human rights. There is perhaps little doubt that the Digital Revolution, as coined in the 1980s, has been a revolution of unequal proportion.

Archaeology is by no means immune to digital inequality, especially as this divide affects both the research design and public dissemination stages of research. This session will explore the following questions:

  • Inequity can be seen in the access that researchers in both private and public institutions have to digital research resources. While the backdrop for this has often been heavily pitted between the Global North with fiscal means, capacity, and technical know-how, and the least developed nations representing the Global South, where many nations are in the process of rebuilding economies, healthcare, and education, within relatively new postcolonial contexts, it is important to acknowledge that that digital exclusion is evident for marginalized groups around the world (UN Habitat 2020). What are the practical implications of such resource limitations in digital research? And what are some of the practical solutions for researchers from areas with limited technological infrastructure?
  • Digital inequality can also result from systemic societal barriers, such as access to education or social pressure, resulting in the exclusion of a large percentage of researchers, heritage practitioners, and members of the public. For example, in the United Kingdom only 19% of university undergraduates in Computer Science are women (Yates and Plagnol 2021). What are the barriers that might keep researchers from participating in the digital revolution? And how does the exclusion of these marginalized populations affect data collection and research project designs in archaeology
  • Finally, we will explore barriers to the dissemination of information, both among researchers and to members of descent or invested communities. This applies particularly to works involving digital heritage and the ownership or copyrights of data produced from the study of objects of cultural patrimony (Sayre 2016, Stobiecka 2020). Are the current open-source coding platforms and free digital data storage sites, such as Github or R-Markdown, enough to ensure equitable information access? And how do these open access forums change the peer review process in archaeological research?

Contributions to the session are expected to do one or more of the following:

  • Highlight the history of the digital revolution within archaeological sciences, the inequalities that have developed, and their current impact on data collection, research project creation, and information dissemination.
  • Explore current digital-based archaeological work, particularly in the context of postcolonial thought, from the perspectives of those practitioners who are actively involved at the local level in lower-resource environments.
  • Confront and challenge disparities in archaeological research participation, opening space for greater dialogue within many disciplines of archaeology and heritage management that are applying new and existing technologies.
  • Examine the potential solutions to digital inequity that researchers have applied in their own research and collaboration.

Our hope is that by the strength of the archaeological research community, we will be able to examine the impacts of digital inequity in archaeology and work towards actionable solutions that participants can implement in their own work.

Prospective participants
This session will be run in the form of a modified roundtable, with a mix of invited discussants and discussants who submit their proposal in the open call. As digital exclusion implicates global practices and policies, the session takes the opportunity to include two to three members involved in not-for-profit, international regulatory bodies expert in heritage and data policies. The session will also include a series of invited flash talks from those working from the ‘other side’ of the divide in order to give as wide a range of voices a platform. These will include heritage professionals from sub-Saharan Africa and South Asia who are currently partners as part of the Mapping Africa’s Endangered Archaeological Sites and Monuments (MAEASaM) and Mapping Archaeological Heritage in South Asia (MAHSA) projects - both of which are funded by the Arcadia Fund.

Format

The session format will be as follows:

  • A position paper will be circulated in advance of the roundtable, which participants are expected to have read in advance of the session
  • Responses will include a small number of discussants (5) (both invited, and the call for discussants will be open), who give longer responses of 10-15 minutes, and 5 short 3-minute lightning talks that will highlight a range of specific examples from invited speakers. These will then form the core material for the discussion.
  • The resulting discussion will be chaired by the organisers, with the discussants given the floor.
  • Following this, the floor will be opened up to those attending the session for comment and questions.
  • Summary to be given by chairs to close out the session.

References

CAWI, C for AWI, Ottowa. 2015. Advancing Equity and Inclusion. 2015. Available at https://www.cawi-ivtf.org/publications/advancing-equity-and-inclusion [Last accessed 14 January 2022].

ITU, Digital Inclusion for all | International Telecommunications Union. Available at https://www.itu.int/en/mediacentre/backgrounders/Pages/digital-inclusion-of-all.aspx [Last Accessed 11 January 2022]

Sayre, Matthew. “Digital Archaeology in the Rural Andes:Problems and Prospects.” In Mobilizing the Past for a Digital Future: The Potential of Digital Archaeology, (eds) Erin Walcek Averett, Jody Michael Gordon, and Derek B. Counts, 183-199. Grand Forks, ND: The Digital Press at the University of North Dakota, 2016.

Stobiecka, M. 2020. Archaeological heritage in the age of digital colonialism, Archaeological Dialogues, 27, 113-125. doi: https://doi.org/10.1017/S1380203820000239

UNESCO 2021. Fostering innovation and inclusive digital transformation for sustainable development. UNESCO, 11 February 2021. Available at https://en.unesco.org/ci-programme/innovation [Last accessed 9 January 2022].

UN Habitat. 2020. World Cities Report 2020: The Value of Sustainable Urbanization | UN-Habitat. 2020. Available at https://unhabitat.org/World%20Cities%20Report%202020 [Last accessed 11 January 2022].

WSIS, World Summit on the Information Society Forum 2021. Available at https://www.itu.int/net4/wsis/forum/2021/ [Last accessed 10 January 2022]

Yates, J and Plagnol, AC. 2021 Female computer science students: A qualitative exploration of women’s experiences studying computer science at university in the UK. Education and Information Technologies DOI: https://doi.org/10.1007/s10639-021-10743-5.

S18: Exploring further the possibilities of 3D Spatial Analysis (Other)

Gary Nobles, Oxford Archaeology

Alexander Jansen, Durham University

James Taylor, University of York

Marina Gavryushkina, Leiden University

Markos Katsianis, University of Patras

#CAASIG3DSA

With the broadly attended virtual meeting in 2021, the CAA’s 3D Spatial Analysis Special Interest Group again welcomes papers which are oriented towards the analysis in 3D space or analysis of 3D space, both theoretically and methodologically.

In this session we want to tackle themes such as:

  • What do 3D and 2.5D approaches afford us beyond traditional 2D perspectives, with innovations in 3D spatial analysis continuing?
  • Why do we, as archaeologists, want to apply 3D spatial analysis, how would we apply it and what questions would it help answer?
  • What added complexities does working in three dimensions bring, how do we make the most of them, and how do we resolve or theorise around such complexities?

Papers are invited which cover any form of 3D spatial data: artefact/object based, recorded geospatial data (GIS/CAD), interpretive 3D modelled data (including procedural/(H)BIM), semantic analysis, and even imagined spaces, this could include their physical manifestations (e.g. Archaeogaming, 3D printing). Crucially, papers should go beyond the presentation of purely 3D recording/modelling methods and processes. What insights can we achieve which are not possible from visual inspection alone? While we would like presentations which push the boundaries (theoretically/technologically), we also welcome position papers. Presenters may want to consider how their research fits within archaeological workflows (established or burgeoning) and broader Spatial Data Infrastructures: what does the integration of associated data bring and what analytical capabilities does or could this create? How do we use these 3D digital objects, datasets and results once they are created? What purpose do they serve, what will their legacy be? Presenters are urged to discuss how the results of 3D spatial analysis are communicated: What are the merits of staying in 3D space against reducing or simplifying it to 2.5D and 2D presentation formats, and vice versa?

Submissions from young researchers/early career researchers are particularly welcome. We want to enable researchers to discuss ideas, whether or not you have access to the best data, funding for big computer systems, or underlying technical knowledge. Such positional papers should focus on what we want to get out of 3D spatial analysis. In this aspect we encourage ‘blue-sky thinking’ particularly if the tools and capabilities are not yet in existence.
Presenters can select one of two formats for their paper: papers which are more exploratory and ‘blue-sky’ in nature may prefer a 10-minute lightning talk format, while those with a more traditional structure may be better suited for a 20-minute standard format. The author(s) should specify their preference when submitting their proposal. If in doubt, contact one of the session organisers well before the paper deadline. The session will conclude with a discussion bringing together the principal themes which emerge from the presented papers, incorporating elements from last year's discussion. Facilitated through the 3D Spatial Analysis CAA SIG, we endeavour to keep these discussions continuing beyond the meetings at CAA International.
S20: Investigating and/or Modelling Ancient Paths: Discussing Theories and Methodologies to achieve Best Practices and Common Standards (Standard)

Francesca Fulminante, UCL & Bristol University, UK; University Roma Tre, Italy

Ulla Rajala, Stockholm University

Joseph Lewis, Cambridge University

Least-cost past analysis, including network least-cost path analysis have developed immensely in the last few decades, also thanks to scholars such as Irmela Herzog and Philip Verhagen . In particular, the least-cost path has become common practice in the reconstruction of paths and routes especially in Pre and Proto-historic times, and the Middle Ages. According to Irmela Herzog, the least cost path is an especially valid instrument for reconstructing paths in those periods.

Recently Farina and Oubina and Joseph Lewis have demonstrated the utility of least-cost path also for predicting without “re-constructing”, roman roads, respectively in northern Spain and highlands and lowlands zones of England. In addition, Oliver Nakoinz and Franziska Paupel have proposed and interesting model, which uses funerary tumuli as landmark to reconstruct paths , but can also be used with different landmarks such as secondary settlements etc. . Similarly, Iza Romanowska and other scholars have recently combined GIS and least-cost path with agent-based modelling . This testifies how least-cost path is still an evolving and dynamic field.

However, we believe that this field is still severely unexplored from a philosophical and methodological perspective: we would like to see papers exploring different premises and interpretations. Can we see the development of more theoretically informed least-cost path analysis? Furthermore, the use of different elevation data sources, algorithms and software packages affects the results and these issues need to be underlined. We should not forget the different cost sources either: does it matter if we use time or energy? And how detailed breakdown we want of our thought moving community: separation according to gender and age?

Least-cost paths are also used in other computerised analyses as an initial step of enquiry: should these applications be problematised? In addition, there is lack of commonly accepted and/or standardised procedures. Therefore, we call for contributions of both theoretical and practical case studies from different regions and timeframe to favour debate and discussion and finally reach hopefully a consensus of best practices and common standard procedures.

References

Davies, Benjamin, Iza Romanowska, Kathryn Harris, and Stefani A. Crabtree. 2019. "Combining Geographic Information Systems and Agent-Based Models in Archaeology: Part 2 of 3." Advances in Archaeological Practice 7 (2):185-193. doi: 10.1017/aap.2019.5.

Faupel, F. 2018. " Reconstructing Early Iron Age Pathways in the Upper Rhine Valley." In Interdisciplinarity and New Approaches in the Research of the Iron Age, Supplementum IV, edited by J. Wilczek, 109-113.

Faupel, F., and O. Nakoinz. 2018. "Rekonstruktion des Wegesystems und Identifikation von Wegparametern der Bronzezeit in Schleswig-Holstein." In Bronzezeitlicher Transport - Akteure, Mittel und Wege, edited by B. B. Nessel, D. Neumann and M. Bartelheim, 149-268. Tübingen.

Fulminante, F. 2022. The Rise of Early Rome: Transportation Networks and Domination in Central Italy, 1050-500 BC. Cambridge: CUP (in press).

Güimil-Fariña, Alejandro, and César Parcero-Oubiña. 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. doi: https://doi.org/10.1016/j.jas.2014.11.030.

Herzog, I. 2013a. "Least-cost networks." In CAA 2012. Proceedings of the 40th Annual Conference of Computer Applications and Quantitative Methods in Archaeology Southampton, 26-30 March 2012, edited by G. Earl, T. Sly, A. Chrysanthi, P. Murrieta-Flores, C. Papadopoulos, I Romanowska and I. Wheatley, 240-51. Amsterdam: Pallas Publications.

Herzog, I. 2013b. "The Potential and Limits of Optimal Path Analysis." In Computational Approaches to Archaeological Spaces, edited by A. / Bevan and M.W. Lake, 179–211. Walnut Creek

Herzog, I. 2014. "A Review of Case Studies In Archaeological Least-Cost Analysis." Archeologia e Calcolatori 25:223-239.

Lewis, J. 2021. "The Suitability of Using Least Cost Path Analysis in the Prediction of Roman Roads in the Highland and Lowland Zones of Roman Britain." Leicester University Presentation.

Verhagen, P. , T. Brughmans, L. Nuninger, and F. Bertoncello. 2013. "The Long and Winding Road: Combining Least Cost Paths and Network Analysis Techniques for Settlement Location Analysis and Predictive Modelling." In CAA2012 Proceedings of the 40th Conference in Computer Applications and Quantitative Methods in Archaeology, Southampton, United Kingdom, 26-30 March 2012, edited by E. Graeme, T. Sly, A. Chrysanthi, P. Murrieta-Flores, C. Papadopoulos, I. Romanowska and D. Wheatley, http://arno.uva.nl/cgi/arno/show.cgi?fid=516092.

Verhagen, P., J. Joyce, and M.R. Groenhuijzen, eds. 2019. Finding the Limits of the Limes. Modelling Demography, Economy and Transport on the Edge of the Roman Empire. Cham: Springer.

Verhagen, P., L. Nuninger, and M.R. Groenhuijzen. 2019. "Modelling of Pathways and Movement Networks in Archaeology: An Overview of Current Approaches." In Finding the Limits of the Limes, Computational Social Sciences, , edited by P. Verhagen, J. Joyce and M.R. Groenhuijzen, 217-249.

S21: Interdisciplinarity in Digital Archaeology (Standard)

Lorna-Jane Richardson, University of East Anglia, School of Art, Media and American Studies

Catriona Cooper, Canterbury Christ Church University

The complex cultural and social concept of authority and expertise is, within the context of archaeology as much as anywhere else, central to the assignment of intellectual authority through expertise to an entity or person. The literature regarding the definition of what constitutes expertise is vast and varied, and encompasses skills, processes, decision-making or knowledge. There has been much work in recent years exploring the interdisciplinarity of digital archaeology (See Huggett (2021) and Morgan (2019)). This session will build on this work, to explore the creation and maintenance of a professional digital archaeological workforce. We will ask, is digital archaeology a distinct discipline, or a smorgasbord of skills, technologies and values; and who defines the expert or the amateur.
Why do some people identify as digital archaeologists, and others do not? What skills are needed to be a 'digital archaeologist'? What is the impact of the ubiquity of computing in the wider archaeological field? Where are the blurred edges of digital archaeology and other disciplines, such as computer science, history, UX, sociology, art, biological sciences etc?

This session will explore the inherent interdisciplinary nature of the field, and aims to invite papers that explore what makes us digital archaeologists:

  • who is included or excluded from this identity,
  • how can we overcome embedded euro-centric and colonial undertones to those involved in the work,
  • how this work can be future-proofed in the face of sectorial challenges and economic pressures.

References

Bevan, A. 2012 'Value, authority and the open society. Some implications for digital and online archaeology' in C. Bonacchi (ed) Archaeology and Digital Communication: Towards Strategies of Public Engagement. London: Archetype, 1-14.

Goffman, E. 1959 The Presentation of Self in Everyday Life. New York: Anchor Books.

Hardwig, J. 1991 'The role of trust in knowledge', Journal of Philosophy 8812, 693-708

Huggett, J. 2021. Archaeologies of the digital, Antiquity 95 (384), 1597-1599

Jacobs, M. and Bosanac, S.E. 2006 The Professionalization of Work. Whitby, ON: De Sitter Publications.

Morgan, C. 2019 Avatars, Monsters, and Machines: A Cyborg Archaeology. European Journal of Archaeology 22(3), 324-337

Richardson, L-J. 2014 Understanding Archaeological Authority in a Digital Context, Internet Archaeology 38. https://doi.org/10.11141/ia.38.1

S22: Traces of digital archaeological practises (Standard)

Isto Huvila, Uppsala University

Zanna Friberg, Uppsala University

Lisa Börjesson, Uppsala University

Olle Sköld, Uppsala University

Knowing about how archaeological work – from fieldwork to data collection, analyses, construction of models, visualisations and beyond – is conducted is essential for understanding its outputs whether they are 3D models, archaeological knowledge, digital or analogue data or books, articles or reports. There is an increasing body of research on the traces of archaeological, and in a broader sense, scientific and scholarly practises. These studies investigate how different traces—conceptualised, for example, as traces (e.g. Hug et al. 2011; Morgan & Eve, 2012), paradata (e.g. Gant & Reilly, 2017; Denard, 2012; Huvila et al. 2021) and provenance metadata (e.g. Huggett, 2014)—can inform data reuse, provide understanding and criticise archaeological practises, documentation and information, seek to understand the limits of archaeological knowledge, and much more. Thematically the work spans from the documentation of archaeological visualisations (Bentkowska-Kafel & Denard, 2012; Börjesson et al. 2020) to studies of the use (Wylie, 2017) and curatorial history of archaeological collections (Voss, 2012; Friberg & Huvila, 2019), archaeological documentation (Huvila et al., 2021), data reuse (Ullah, 2015; Sobotkova, 2018; Strupler, 2021), analysis of earlier data collection methods (Olson & Walther, 2007) and changing data practises (Montoya et al., 2019).

This session invites presentations of evidence-based, theoretical and reflective work relating to traces of digital archaeological practises. Theoretically, the session is open to perspectives drawing from the quantitatively oriented trace data analysis tradition and qualitative investigation of traces—including trace ethnography that enables identification and analysis of traces in semi- or unstructured documentary formats such as working notes, log files and oral communication (cf. Geiger & Ribes, 2011)—and beyond to bring different approaches and theoretical views into discussion with each other. Contributions to the session can, for example, describe qualitative and quantitative methods and experiences of collecting traces (including paradata, provenance metadata and beyond); discuss how traces can inform data reuse, analysis and use of archaeological information and knowledge in different forms; engage in theoretical ruminations of what counts and works as a trace; share experiences and considerations of e.g., what functions as a trace and why, what types of traces are informative and for what purposes, and what kinds of traces can be seemingly informative but in practice are less useful. Thinking of possible contexts, the discussed work can pertain to fieldwork and documentation of digital field practises, documentation of data creation (e.g. database design and curation), traces of practises in legacy data, metadata and paradata, automatic and manual documentation of practises in field and lab notebooks, databases and video diaries, annotation of 3D visualisations and documentation and archiving of software used in archaeological data capturing and analysis. The disciplinary background of proposers includes the whole CAA community from archaeologists to, for example, social and computer scientists, heritage, museum and information studies researchers and practitioners.

The format of the session (Standard session) consists of paper presentations and discussion, including a concluding open forum for sharing and collecting ideas for future research on and in relation to traces of digital archaeological practises.

The session is affiliated with the CAASIG-ARKWORK on archaeological practises and knowledge work in the digital environment.

References

Bentkowska-Kafel, A., Denard, H., & Baker, D. (Eds.). (2012). Paradata and transparency in virtual heritage. (A. Bentkowska-Kafel, H. Denard, & D. Baker). Farnham: Ashgate.

Börjesson, L., Sköld, O., & Huvila, I. (2020). The politics of paradata in documentation standards and recommendations for digital archaeological visualisations. Digital Culture and Society , 6 (2), 191–220. https://doi.org/10.14361/dcs-2020-0210

Denard, H. (2012). A new introduction to the London Charter. In A. Bentkowska-Kafel, H. Denard, & D. Baker, A. Bentkowska-Kafel, H. Denard, & D. Baker (Eds.), Paradata and transparency in virtual heritage (pp. 57–71). Farnham: Ashgate.

Friberg, Z., & Huvila, I. (2019). Using object biographies to understand the curation crisis: lessons learned from the museum life of an archaeological collection. Museum Management and Curatorship , 34 (4), 362–382. https://doi.org/10.1080/09647775.2019.1612270

Gant, S., & Reilly, P. (2017). Different expressions of the same mode: a recent dialogue between archaeological and contemporary drawing practices. Journal of Visual Art Practice , 17 (1), 100–120. https://doi.org/10.1080/14702029.2017.1384974

Geiger, R. S. & Ribes, D. (2011). Trace Ethnography: Following Coordination through Documentary Practices. In Proceedings of the 44th Annual Hawaii International Conference on System Sciences (HICSS). http://www.stuartgeiger.com/trace-ethnography-hicss-geiger-ribes.pdf

Hug, C., Salinesi, C., Deneckere, R., & Lamasse, S. (2012). Process modeling for Humanities: tracing and analyzing scientific processes. In M. Zhou, I. Romanowska, Z. Wu, P. Xu, & P. Verhagen (Eds.), Annual Conference of Computer Applications and Quantitative Methods in Archaeology (CAA 2011) (pp. 245–255). Amsterdam: Amsterdam University Press.

Huggett, J. (2014). Promise and Paradox: Accessing Open Data in Archaeology. In C. Mills, M. Pidd, & E. Ward, C. Mills, M. Pidd, & E. Ward (Eds.), Proceedings of the Digital Humanities Congress 2012. Studies in the Digital Humanities. Sheffield: HRI Online Publications.

Huvila, I., Sköld, O., & Börjesson, L. (2021). Documenting information making in archaeological field reports. Journal of Documentation, 77(5), 1107–1127. https://doi.org/10.1108/JD-11-2020-0188

Morgan, C., & Eve, S. (2012). DIY and digital archaeology: what are you doing to participate? World Archaeology , 44 (4), 521–537. https://doi.org/10.1080/00438243.2012.741810

Montoya, R. D., Morrison, K., & Morrison, K. (2019). Document and data continuity at the Glenn A. Black Laboratory of Archaeology. Journal of Documentation, 75(5), 1035–1055. http://dx.doi.org.ezproxy.its.uu.se/10.1108/JD-12-2018-0216

Olson, C., & Walther, Y. (2007). Neolithic cod and herring fisheries in the Baltic Sea, in the light of fine-mesh sieving: A comparative study of subfossil fishbone form the late Stone Age sites at Ajvide, Gotland, Sweden and Åland, Finland. Environmental Archaeology, 12(2), 175–185.

Sobotkova, A. (2018). Sociotechnical Obstacles to Archaeological Data Reuse. Advances in Archaeological Practice, 6(2), 117–124. https://doi.org/10.1017/aap.2017.37

Strupler, N. (2021). Re-discovering Archaeological Discoveries. Experiments with reproducing archaeological survey analysis. Internet Archaeology, 56, Article 6. https://doi.org/10.11141/ia.56.6

Ullah, I. I. T. (2015). Integrating older survey data into modern research paradigms. Advances in Archaeological Practice, 3(4), 331–350. https://doi.org/10.7183/2326-3768.3.4.331

Voss, B. L. (2012). Curation as research. A case study in orphaned and underreported archaeological collections. Archaeological Dialogues, 19(2), 145–169. https://doi.org/10.1017/S1380203812000219

Wylie, A. (2017). How Archaeological Evidence Bites Back: Strategies for Putting Old Data to Work in New Ways. Science, Technology, & Human Values, 42(2), 203–225.

S23: Computational Archaeology & Seafaring Theory (Roundtable)

Emma Slayton, Carnegie Mellon University

Marisa Julia Borreggine, Harvard University

R. Helen Farr, Southampton University

Katherine Jarriel, Purdue University

Justin Leidwanger, Stanford University

Archeologists and anthropologists have long discussed the spaces of human movement over larger bodies of water. In the past several decades, with the advance of computational analysis, this conversation has expanded to include how modeling sea travel might lead to new insights about societal organization, technology development, and communication methods. At institutions across the globe, scholars are using numerous methods to address research questions about movement by sea, ancient and historical ocean resource usage, and the broad role of human-ocean interaction in past communities. We have newly entered the United Nations Decade of Ocean Science for Sustainable Development (2021 - 2030), which aims to “change humanity’s relationship with the ocean”. Ocean navigation is an inherently collective, social process. This roundtable will address what modeling methods are currently being employed or are needed to capture past maritime mobilities as well as show how to incorporate the social dynamics of interaction in maritime spaces. As we become more confident in our methods and move beyond solely relying on least-cost pathways and other methods that raise questions of environmental determinism, we are simultaneously co-constructing our practice and theory. This session aims to bring together a diverse and interdisciplinary cohort of archeologists and anthropologists to collectively assess the state of computational archeology and seafaring practice and theory in order to establish a next phase of future research that can address these major challenges in our field.

The scholarship on seafaring modeling is undertaken by scholars who are otherwise dispersed among various academic departments and geographical locations worldwide. Often scholars working on similar methods are unaware of one another due to these divides. Lack of discoverability of relevant scholarship has been a hindrance in developing a unified field of seafaring modeling. We see a timely need to define the state of the field, establish its future directions, and bridge gaps in scholarly networks to uncover connections or disconnects in how we address both computational methods and practice as well as the underlying anthropological theory that is critical to future modeling of seafaring space. We aim to challenge prior conceptions of computational modeling as a field devoid of human perspective and solely focused on environmental determinism, to reference how the human element and inherently social practice of seafaring can be incorporated into various modeling strategies from isochrone approaches to agent based modeling. We recognize that the sea is a space of being and meaning, and that discussions of human motivation, social structures, and technological capabilities all play a role in not only the movement of peoples across the sea but also in how researchers can model diverse uses of these spaces.

One focus of this session will be on the methods currently employed by researchers to model maritime mobility. This includes working through the basic elements of importance related to what climate (forecasted, sub sampled, etc.) data sets are used within different frameworks, what technological aspects of vessels need to be considered as base factors within computational models, how many runs is enough runs, what are the positives of using different computational approaches (isochrone vs. least-cost pathway vs agent-based modeling), etc. In addition, though similar to previous sessions and the current session 27 “name of Phadeon’s session” that have devoted space to modeling past movement across the seas, this roundtable seeks to also discuss the challenges faced by the field to capture the humanist elements of past voyages through discussion of those actively engaged in this research. We aim to review in depth the balance between computational and humanistic elements of seafaring modeling, and promote the integration of diverse ways of knowing, mapping, and experiencing space. Interaction across and with the sea is a deeply social process. There are many factors that affect relationships within vessels on the sea, people on land, and the water around them. The underpinning computational models must engage with human agency, decision making, and past seafaring practice. During the roundtable, we will hold a discussion between panelists and the audience to address the relationship between computational modeling and anthropological theory. We will consider the ways in which researchers can understand human agency in the past and use it to build computational models that reflect a more nuanced human experience. For example, panelists will touch on how navigational skill and knowledge impact seafaring choices (and thus the basis for a navigational model). Many computational tools are built upon western assumptions of spatiality, so moving our field to incorporate Iindigenous, non-western, and other culturally-specific understandings of space can allow for the production of models that deliberately tie together cultural context and spatial patterning. Through this initial discussion, we seek to build the groundwork for approaches that can help decolonize or de-westernize the discussion of past seafaring efforts by focusing on Indigenous perspectives, breaking down constructs of national land boundaries, and acknowledging the existence of multiple seascapes within modern mapped seas or oceans. Other topics include: sea spaces as embodied ‘land’scapes, the role of phenomenology in evaluating mobility, the ways knowing or wayfinding impact routes taken, the effect of stochastic environmental conditions on human decision-making, and consideration for how to discuss the lives of past climate refugees.

Once the general bounds of theory and computational strategies are defined, in part within this session, those present will be asked to help define the state of the field moving forward from this roundtable. We want our participants to recognize that the tools we use and outcomes we observe from modeling serve mainly as a basis to ask more questions about the human experience, and as such we hope to push the field towards a broader evaluation of how theory affects computational modeling. This roundtable will also serve as space to discuss topics needed for future discussions, particularly those held at an upcoming Computational Archeology & Seafaring Theory (CAST) workshop to be held at Stanford University in late Fall 2022. For questions regarding this workshop, please email castworkshop2022@gmail.com. Additionally, this session will be the first to tie into the new Special Interest Group Computationally Modeling Water-based Movement (CMWM).

The goal of this roundtable session is to foster broader discussions of connections between modeling practice and theory, as well as aspects of how to further develop and support effective computational seafaring modeling. By bringing together interdisciplinary archeological practitioners from around the globe, this session will develop a vibrant network of scholars, who not only innovate in maritime computational modeling, but who actively work toward developing the future of the field. In connecting people doing similar research, the roundtable will foster collaborations for future scholarship. Experiencing the diverse disciplinary, geographical, theoretical, and methodological perspectives of peers will further revitalize the work we are currently doing. Once in the same space, these researchers can not only identify key areas still needed to be discussed in the field, what practices are effective or ineffective in modeling water based mobility, who is focusing on this topic and in what contexts, and how we can move forward as a field as a community.

We invite those who wish to be members of the roundtable to submit either a written position statement (maximum 1000 words plus references) that can be read in advance of the session by other participants.

References

Borreggine, M., Powell, E., Pico, T., Mitrovica, J. X., Meadow, R., & Tryon, C. (2022). Not a bathtub: A consideration of sea-level physics for archaeological models of human migration. Journal of Archaeological Science, 137, 105507.

Davies, B., Bickler, S. H., & Traviglia, A. (2015). Sailing the simulated seas: A new simulation for evaluating prehistoric seafaring. Across Space and Time: Papers from the 41st Conference on Computer Applications and Quantitative Methods in Archaeology, Perth, 25–28 March 2013, 215–223. Amsterdam: Amsterdam University Press.

Gosden, C., & Pavlides, C. (1994). Are islands insular? Landscape vs. Seascape in the case of the Arawe Islands, Papua New Guinea. Archaeology in Oceania, 29(3), 162–171.

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

Laituri, M. (2011). Indigenous peoples’ issues and indigenous uses of GIS. The SAGE Handbook of GIS and Society, 1996, 202–221.

Lewis, D. (1994). We, the navigators: The ancient art of landfinding in the Pacific. University of Hawaii Press.

Lock, G., & Pouncett, J. (2017). Spatial thinking in archaeology: Is GIS the answer? Journal of Archaeological Science, 84, 129–135.

Slayton, E., & Smith, K. (2021, July). Moving Over Seas: Modeling Seafaring Routes to Analyze Past Connections. Presented at the Computer Applications and Quantitative Methods in Archaeology, Cyprus.

S24: Stay connected: Developing Mobile GIS for team-based collaborative networking in archaeological research (Other)

Guiseppe Prospero Cirigliano, University of Siena, Department of History and Cultural Heritage

Nazarij Bulawka, University of Warsaw. Antiquity of Southern Europe Research Centre / University of Warsaw. Institute of Archaeology

Julia Chyla, University of Warsaw. Antiquity of Southern Europe Research Centre / University of Warsaw. Institute of Archaeology

Adéla Sobotkova, Aarhus University, School of Culture and Society

This Special Interest Group, in its previous CAA conference editions (2017, 2018, 2019, 2021), has drawn attention to the increasing importance of Mobile GIS not only in archaeology but in the field mapping process in general, which has been contributing to a substantial evolution of fieldwork methodology and data collection process (Buławka and Chyla,2020). In this edition, we would like to focus on how the use of this mobile GIS technology, especially in archaeology evolved in recent years. As a result of the COVID emergency, we started to explore different research workflows, also in archaeological field prospecting and postprocessing data collected in such a manner. The possibility of having access to data and sharing them each independently on our device could also provide important help in respecting the recommendations to which we are now accustomed (Sobotkova et al., 2021).

Additionally, the current differences in collaborative solutions between open-source and commercial software will be discussed. Does the different OS and software entail a different working organization? What are the aspects and the reasons that lead a research team to choose an OS or software rather than another? Are all applications secured for future use? Can we foresee, that OS update, hardware compatibility, or financing of the application can affect our ability to use the same workflow in the future?

Another very important aspect that we would like to address at CAA 2022 is understanding how mobile devices have allowed us to improve fieldwork efficiency, but also, how it has transformed the essence of the working process. So, we would answer questions such as: What are the advantages and critical issues of the use of Mobile GIS in archaeology? How can the use of these devices improve teamwork in the field? How has data sharing and data management changed?

This session welcomes articles from research at various levels: it’s also open to student projects, Bachelor, Master, and PhD thesis, and the results of preliminary research. When submitting please specify if you want to present a long (15 minutes) or short (10 minutes) paper.
The session invites papers that may concern methodological and technical aspects and will be finished with a moderated discussion.

Keywords

Mobile GIS; fieldwork; teamwork; surface prospection

References

Buławka, Nazarij, and Julia Maria Chyla. 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.

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.

S25: Engaging the Public with Archaeology and Cultural Heritage: Exploring and Assessing Outreach during the COVID-19 Pandemic (Standard)

Lisa Fischer, Independent Scholar

The COVID-19 pandemic has disrupted many facets of life over the past two years. As a result, museums, universities, and historical sites have had to grapple with closures, budget cuts, and protecting the health of staff and visitors while trying to fulfil their educational missions. During lockdowns, heritage organisations had to focus their outreach and engagement efforts almost exclusively on online channels. This led to a push of new educational offerings, from zoom lectures to circulating lists of online archaeological resources for schools. While many of these digital assets were made available freely on the internet, some cultural heritage organisations experimented with monetizing virtual content to try to counter revenue losses caused by the lack of in-person visitors. Posting educational materials on the web and social media was not new, but many organisations and individuals increased their output to engage the public stuck at home and to provide educational resources to students as well as teachers engaged in virtual learning. At the same time, staff were also challenged to develop this new content, often while working from home without access to their sites, objects, and office resources.

Museums and historical sites, as they were able to re-open to the public, were suddenly faced with new challenges regarding how to create a safe on-site visit. High-contact, embedded touchscreens and hands-on activities were suddenly seen as potential virus vectors. Interpretative approaches—like video screens and immersive technology experiences—that may have previously encouraged guests to cluster in groups, had to be adapted to new physical distancing measures or face temporary shuttering. Organisations, especially those that rely on ticket sales for revenue, had to find ways to foster visitation while offering programs that met new health and safety guidelines.

Challenging situations, like Covid-19, can often spur creativity and offer the opportunity to analyse old and new ways of working. This session invites authors to discuss and assess current technology-based approaches created during the pandemic for engaging the public, teachers, and students with cultural heritage. Papers can examine digitally-based educational approaches through any channel, including the web, social media, in the classroom, or on-site. What have we learned during the pandemic about how to effectively deliver information about archaeology and sites online and/or in-person? How do we evaluate digital resources and determine whether they are meeting the needs of the intended audience(s)? What approaches that worked well before and/or during the pandemic should continue and what new challenges are being faced now? What lessons have been learned from approaches that did not go quite as planned or even failed? Can a glut of online resources result in oversaturation and how should organisations assess the effectiveness of outreach approaches, especially in the face of limited budgets? How do we balance the costs of developing and maintaining technology-based educational resources while making them as accessible to audiences as possible?

This session will appeal to cultural heritage practitioners interested in how technology can be used to effectively educate and engage non-specialist audiences with archaeology. Papers are invited from authors who would like to explore some of these questions in the context of their own research. This can be done by presenting new applications, resources, projects, and strategies “born” during the pandemic to illustrate how organisations adapted their interpretive approaches. Example projects can be in any stage of development, including planning, in progress, or completed. Authors can also focus on the bigger picture to evaluate pandemic-related trends—across institutions and/or platforms—in technology-based outreach and education focusing on cultural heritage topics. Papers may also examine future directions and the potential long-term impact that the pandemic may have on technology use, both online and on-site.

References

Network of European Museum Organisations (NEMO)

  • 2020 Survey on the impact of the COVID-19 situation on museums in Europe: Final Report. https://www.ne-mo.org/fileadmin/Dateien/public/NEMO_documents/NEMO_COVID19_Report_12.05.2020.pdf.
  • 2021 Follow-up Survey on the Impact of the COVID-19 Pandemic on Museums in Europe. https://www.ne-mo.org/fileadmin/Dateien/public/NEMO_documents/NEMO_COVID19_FollowUpReport_11.1.2021.pdf.

International Council of Museums (ICOM)

  • 2020 Museums, Museum Professionals and Covid-19. https://icom.museum/wp-content/uploads/2020/05/Report-Museums-and-COVID-19.pdf.
  • 2020 Museums, Museum Professionals and Covid-19: Follow-up Survey. https://icom.museum/wp-content/uploads/2020/11/FINAL-EN_Follow-up-survey.pdf.
  • 2021 Museums, Museum Professionals and Covid-19: Third Survey. https://icom.museum/wp-content/uploads/2021/07/Museums-and-Covid-19_third-ICOM-report.pdf

United Nations Educational, Scientific and Cultural Organization (UNESCO)

  • 2021 Museums around the World in the Face of COVID-19. https://unesdoc.unesco.org/ark:/48223/pf0000376729_eng?posInSet=2&queryId=b1541953-7be1-4f65-8af6-f9b25bccaa69.
  • 2021 World Heritage in the Face of COVID-19. https://unesdoc.unesco.org/ark:/48223/pf0000377667?posInSet=1&queryId=bd741d77-d5ef-4c62-b83b-bfaf040b7b32.
S27: Modeling maritime mobility: State-of-the-art and ways forward (Standard)

Phaedon Kyriakidis, Cyprus University of Technology

Elias Gravanis, Cyprus University of Technology

Stella Demesticha, University of Cyprus

Christian Reepmeyer, University of Cyprus

Theodora Moutsiou, University of Cyprus

Daniella Bar Yosef-Mayer, Tel Aviv University

Angelos Hliaoutakis, Foundation for Research and Technology – Hellas

Vassilis Zervakis, University of the Aegean

Kostas Theodorou, University of the Aegean

Elena Xoplaki, Justus-Liebig-University Giessen

Dan Montello, University of California Santa Barbara

Seaborne movement underpins frontier research inquiry in archaeology, such as water-crossings in the context of human dispersals, seagoing, seafaring and island colonisation (Anderson, 2010). Yet it also controls the degree of seaborne-interaction between origin and destination locations, which in turn is essential for understanding maritime networks, such as raw material circulation or trade networks (Leidwanger and Knappett, 2018). Maritime mobility is broadly controlled by geographical context, weather conditions, demographics, motivation for undertaking a trip which in turn controls destination selection and possibly risk attitude, navigation capabilities, as well as marine, e.g. vessel, technology. Mobility in general can be distinguished into potential and realized mobility, the latter being typically associated with verified presence of common or similar material culture at origin and destination locations corroborating movement between these locations.

Modeling efforts focusing on seaborne movement based on computer simulations, closely related to agent-based models (Romanovska et al., 2021) – although not always explicitly stated as such, have been often used to testarchaeological hypotheses related to colonisation, migration, and culture contact (Davies and Bickler, 2015; Montenegro et al. 2016; Norman et al., 2018; Bird et al., 2019). In such simulations, multiple “virtual vessels” embark from coastal locations and interact in a stochastic or deterministic way with winds and currents according to their structural characteristics and the motivation (destination) of the navigator. Such “vessels” could equally well represent individuals swimming or paddling (Hölzchen et al., 2022). The frequency and location of successful landings, as well as the trajectories followed, offer valuable insights in terms of probabilities of connections between possible origins and destinations along with the pattern of maritime routes followed.

A second family of models employ Least Cost Path (LCP) analysis modified to account for the maritime environment(Gustas and Supernant, 2017; Kealy et al., 2018; Gal et al., 2021a, b; Arcenas, 2021; Perttola, 2021, McLean and Rubio-Campillo, 2022). In LCP analysis, one first defines a “cost surface” pertaining to the cost (in terms of effort or time required) associated with moving from one location/node to an adjacent location. An “accumulated cost surface” is then computed, corresponding to the cost of moving from a particular starting location (source) to any other node of the domain. Lastly, the optimal sequence of steps along the nodes is determined, a shortest or fastest path, linking the source location with a given destination node. Closely related to LCP approaches are models based on the concept of isochrones, tracing the locus of potential arrivals over a given time interval (Slayton, 2018; Safadi and Sturt, 2019).

A third family of models pertains to the estimation of the intensity of potential mobility between network nodes based on information on node characteristics (e.g. settlement size) and intervening distances, and includes adaptations of gravity-type models in a maritime context (Knappett, 2018).

Existing computational models of maritime mobility, however, are not without problems. LCP approaches, for example, implicitly assume perfect knowledge of weather conditions, typically reporting a single optimal route without exploring the variability of the remaining solutions (Dickinson et al., 2019). Often the application of models is undertaken usingrather coarse spatial resolution data of weather variables, and/or time-averages of those data; this often results to overly smooth trajectories and travel time underestimation. In addition, most models use present day descriptions of weather conditions, which serve as proxies for the corresponding conditions in times; exceptions are model applications that are cast explicitly in a paleoenvironmental context, such as the colonization of Sahul. Agent-based models of seaborne movement do not typically incorporate cognitively-informed parameterizations of navigation capabilities, such as visibility, landmark recognition, or path planning strategies. Lastly, computational models of potential maritime mobility are not yet coupled to models of realized mobility (maritime networks of material culture), or to models of (meta)population dynamics, and furthermore to models of (meta)population genetics; the latter two families of models represent frontier research in fields such as ecology and biology (e.g. Bradburd and Ralph, 2019; Bradshaw et al., 2021).

With this session we aim to showcase state-of-the-art methods pertaining to modeling maritime mobility, and in conjunction with roundtable session #23 (Computational Archaeology & Seafaring Theory) provide a forum for presenting new modeling efforts. We particularly invite Early Career Researchers and student presenters to share with us new ideas and ongoing projects. Participants are invited to present their research in a 20 minute format (15 min presentation and 5 minutes discussion) and also consider contributing to roundtable session #23 – Computational Archaeology & Seafaring Theory.

References

Anderson, A. (2010): The origins and development of seafaring: Towards a global approach, in: A. Anderson, J.H. Barrett, and K.V. Boyle (Eds), Global Origins and Development of Seafaring. McDonald Institute Monographs, University of Cambridge.

Arcenas, S.L. (2021): Mare ORBIS: A network model for maritime transportation in the Roman world, Mediterranean Historical Review, 36(2), 169-198.

Bird, M.A., Condie, S.A., O’ Connor, S. et al. (2019): Early human settlement of Sahul was not an accident, Nature Scientific Reports, 9, 8220.

Bradburd, G.S., and Ralph, R.L. (2019): Spatial population genetics: It’s about time, Annual Review of Ecology, Evolution, and Systematics, 50, 427-449.

Bradshaw, C.J.A., Norman, K., Ulm, S. et al. (2021): Stochastic models support rapid peopling of Late Pleistocene Sahul. Nature Communications, 12 2440.

Davies, B., and Bickler, S. (2015): Sailing the simulated seas: A new simulation for evaluating prehistoric seafaring, In, Traviglia, A. (Eds.), Across Space and Time, Papers from the 41st Conference on Computer Applications and Quantitative Methods in Archaeology, p. 215-223, Perth, 25-28 March 2013. Amsterdam University Press.

Dickinson, T., Farr, H., Sear, D., and Blake, J.I.R. (2019): Uncertainty in maritime weather routing, Applied Ocean Research, 88, 138-146.

Gal, D., Saaroni, H. and Cvikel, D. (2021a):  A new method for examining maritime mobility of direct crossings with contrary prevailing winds in the Mediterranean during antiquity, Journal of Archaeological Science, 129: 105369.

Gal, D., Saaroni, H. and Cvikel, D. (2021b):  Measuring potential coastal sailing mobility with the loose-footed square sail, Journal of Archaeological Science, 136: 105500.

Gustas, R., Supernant, K. (2017): Least cost path analysis of early maritime movement on the Pacific Northwest Coast, Journal of Archaeological Science, 78, 40-56.

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Kealy, S., Louys, J., and O’Connor, S. (2018): Least-cost pathway models indicate norther human dispersal from Sunda to Sahul, Journal of Human Evolution, 125, 59-70.

Knappett, C. (2018): From network connectivity to human mobility: Models for Minoanization, Journal of Archaeological Method and Theory, 25(4), 974-995.

Leidwanger, J., and Knappett, C. (2018): Maritime Networks in the Ancient Mediterranean World, Cambridge University Press.

McLean, A., and 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.

Montengro, A., Callaghan, R.T., and Fitzpatrick, S.M. (2016): Using seafaring simulations and shortest-hop trajectories to model the prehistoric colonization of Remote Oceania, Proceedings of the National Academy of Sciences, 113(45), 12685-12690.

Norman K., Inglis, J., Clarkson, C. (2018): An early colonisation pathway into northwest Australia 70-60,000 years ago, Quaternary Science Reviews, 180, 229-239.

Perttola, W. (2021): 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,  https://doi.org/10.1007/s10816-021-09534-6.

Romanowska, I., Wren, C.D., and Crabtree, S.A. (2021): Agent-based Modeling for Archaeology: Simulating the Complexity of Societies, The Santa Fe Institute Press.

Safadi, C., and Sturt, F. (2019) The warped sea of sailing: Maritime topographies of space and time for the Bronze Age eastern Mediterranean, Journal of Archaeological Science, 103, 1-15.

Slayton, E. (2018): Seascape Corridors: Modeling Routes to Connect Communities across the Caribbean Sea, Sidestone Press.

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