The approved sessions for CAA2023 are listed here. Click on the session title for more information.
S01. Integrating mobile computing technologies into traditional archaeological methods
|Prof Gideon Shelach-Lavi, Hebrew University of Jerusalem|
Dr Ying Tung Fung, Hebrew University of Jerusalem and University of Oxford
Session type: Standard
Although mobile computing is not new to field archaeology (Ancona et al. 1999), it is not until the past two decades mobile devices and applications have become more common. This gives us a more efficient way to collect and record data and allows us to put data in relational contexts easily (Wallrodt, 2016). The digitalising technique is replacing the traditional paper forms in a positive way, but it is still evolving and needs improvement for a better integration between the design of mobile applications and conventional archaeological collection and recording methods. Archaeological projects usually involve a large amount of data, which cannot be easily recorded, organised and stored without any hassle. Mobile devices and applications provide many benefits for data collection process as survey and excavation points and polygons can be marked in software such as ArcGIS and GPS applications in advance. Data can be recorded and uploaded by multiple team members to mobile devices offline and then to computational devices to build up master datasets and relational databases, which are ready to be used for computational analysis.
However, paperless documentation is still new and there are still obstacles we have to overcome. For example, we have several cases of using mobile devices such as PDA and iPad (e,g, Canals et al., 2008; Ellis, 2016; Gordon et al., 2016; Motz, 2016) as well as custom-developed mobile application (e.g. Fee, 2016) to record data, but these applications have their limitations and challenges. Developing a new application requires extra works and cost to make it available on different operation systems and future maintenance are needed for long-term project, while using existing software limits the ways of which data are recorded and collected for specific archaeological project (Wallrodt, 2016). There are also technical problems such as features setting, choosing a suitable database model and exporting data to computational devices (Fee, 2016), and problems in applying the digital methods in different regions around the world especially the developing regions (Sayre, 2016).
Along with the continuous advancement of mobile applications and devices in recent years, the above issues have been minimised. Open-source applications such as FAIMS Mobile and HumanOS provide customisation services for specific projects (Ballsun-Stanton et al., 2018; Colleter et al., 2020). Other free and open-access applications such as DigApp and TaphonomApp allow a more flexible operation as they can be easily modified by users (Martín-Perea et al., 2020). The innovation of the device iPhone 12 pro LiDAR, meanwhile, provides a new way to scan and record features using mobile devices (Cohen-Smith et al., 2022). It is timely to evaluate the advantages and limitations of applying these new applications and devices in archaeological research, and how to better integrate mobile computing methods with traditional archaeological recording methods.
This session welcomes papers that discuss and evaluate the new mobile applications and devices in archaeological collection and recording processes. The topics include, but not limited to: the use and review of innovative mobile devices and applications in archaeological projects, the benefits, limitations and challenges of using these applications and devices. As well as how to overcome or minimise problems to improve the integration of mobile computing technologies with traditional archaeological methods, and suggestions and prospects for future development of using mobile computing in archaeology.
Ancona, M., Dodero, G. and Gianuzzi, V., 1999, September. RAMSES: a mobile computing system for field archaeology. In International Symposium on Handheld and Ubiquitous Computing (pp. 222-233). Springer, Berlin, Heidelberg.
Canals, A., Rodríguez, J. and Sánchez, R., 2008. The 3COORsystem for data recording in archaeology. Journal of Anthropological Sciences, 86, pp.133-141.
Caraher, W., 2016. Slow archaeology: Technology, efficiency, and archaeological work. Mobilizing the past for a digital future: The potential of digital archaeology. Part 4.1.
Ellis, S.J., 2016. Are we ready for new (digital) ways to record archaeological fieldwork? a case study from Pompeii. Mobilizing the past for a digital future: The potential of digital archaeology. Part 1.2.
Fee, S.B., 2016. Reflections on Custom Mobile App Development for Archaeological Data Collection. Mobilizing the past for a digital future: The potential of digital archaeology. Part 2.1.
Gordon, J.M., Averett, E.W., Counts, D.B., Koo, K. and Toumazou, M.K., 2016. DIY Digital Workflows on the Athienou Archaeological Project, Cyprus. Mobilizing the past for a digital future: The potential of digital archaeology. Part 1.4.
Motz, C.F., 2016. Sangro Valley and the Five (Paperless) Seasons: Lessons on Building Effective Digital Recording Workflows for Archaeological Fieldwork. Mobilizing the past for a digital future: The potential of digital archaeology. Part 1.3.
Sayre, M., 2016. Digital Archaeology in the Rural Andes: Problems and Prospects. Mobilizing the past for a digital future: The potential of digital archaeology. Part 1.6.
Wallrodt, J., 2016. 1.1. Why Paperless: Technology and Changes in Archaeological Practice, 1996–2016. Mobilizing the past for a digital future: The potential of digital archaeology. Part 1.1.
S02. Studying uncertainties in archaeology: A new research agenda
Eduardo Herrera Malatesta, Center for Urban Networking Evolutions, Aarhus University
Tom Brughmans, Center for Urban Networking Evolutions, Aarhus University
Session type: Standard
Archaeology and landscape research have greatly benefited from the increasing application of computational methods over the past decades. Geographical Information Systems (GIS) and spatial statistical methods such as point patterns have been revolutionary for the discipline. Furthermore, the analytical power of studying spatial relationships between objects has been enhanced through the use of network science for archaeological landscape research. However, the results obtained from these techniques can be greatly affected by the many uncertainties imposed by the fragmentary nature of archaeological data, particularly when they are derived from non-systematic surveys. Since the 1960s, archaeologists have tried to solve this by developing more systematic fieldwork methodologies such as total-area survey strategies. Yet, this methodology cannot be applied to every region; therefore, non-systematic survey strategies must be followed. This poses methodological challenges when attempting to apply GIS, spatial statistics and network analysis methods to such fragmentary and uncertain datasets.
For example, while in archaeology it is common to use statistical methods to deal with partial data in point pattern analysis to study regional patterns, this does not provide information to assess the actual levels of uncertainty of a particular regional dataset. Furthermore, at the moment there is no formal study of the uncertainty levels for the computational models resulting from applying the mentioned methods to a non-systematic regional dataset. While the study of uncertainties has seen recent debates in archaeology, it is still an underdeveloped topic. Particularly, previous attempts of quantifying uncertainties for archaeological data have not aimed at creating overarching solutions or resources tailored for the discipline, i.e., a protocol or software.
This session aims at bringing together contributions that present concrete and original research on the quantification of archaeological uncertainties from any archaeological spatial and temporal perspective. Contributions should look towards the creation of overarching solutions for archaeological uncertainties and for the formal application of uncertainty methods and analysis. For this, each presentation should contain 1) a concrete research problem and case study, 2) a concrete description of the used methods, 3) a clear walkthrough of the application of the methods (with accompanying code when available), 4) concrete results, and 5) a concrete discussion on the interoperability of their methods and results for other case studies. Paper topics of particular interest to this session include but are not limited to:
- Systematic description of sources of and types of uncertainties in archaeological data,
- Uncertainty in landscape archaeology,
- Uncertainty in network research,
- Methods for quantifying uncertainties,
- Sensitivity analysis approaches,
- Protocols, methodological pipelines or standards for uncertainty quantification,
- Coded implementation of uncertainty quantification methods,
- Aggregation of uncertainty quantification methods in toolboxes for our community,
- Case studies addressing the above for any region or time period.
This session will provide a platform for sharing experiences, strategies, and methods for archaeological research on uncertainties. Our ultimate aim is, together with the participants, to outline a new research agenda for the formal application of uncertainty quantification methods, for both non-systematic survey data and computational models, in archaeology.
S03. Our Little Minions pt. V: small tools with major impact
Moritz Mennenga, Lower Saxony Institute for Historical Coastal Research, Wilhelmshaven, Germany
Ronald Visser, M.A., Saxion University of Applied Sciences, Deventer, Netherlands
Brigit Danthine, M.A., Austrian Archaeological Institute (Austrian Academy of Science), Austria
Florian Thiery, M.Sc., Römisch-Germanisches Zentralmuseum, Mainz, Germany
Session type: Lightning talks (max 10 minutes)
In our daily work, small self-made scripts (e.g. Python, R, Bash, Haskell), home-grown small applications (e.g. GIS Plugins) and small hardware devices significantly help us to get work done. These little helpers -“little minions” – often reduce our workload or optimize 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. As we have seen in last year’s “minion talks” since 2018 there is a wide range of tools to be shared. This already fifth Little Minion session invites short presentations, lightning 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 fieldwork or excavation technology, associated evaluation or methodical approaches in archaeology. Each talk should explain the innovative character and mode of operation of the digital tool. The only restriction is that the software, source code and/or building instructions are open and are or will be freely available. Proprietary products cannot be presented, but open and freely available tools designed for them. In order to support the subsequent use of the tools, the goal should be that they are openly and available to the scientific community (e.g. GitHub, GitLab). We invite speakers to submit a short abstract including an introduction to the tool, the link to the repository – if possible – to get access to the source code and an explanation of which group of researchers could benefit from the little minion and how. The tools may address the following issues, but are not limited to (you will find an overview of the previous sessions under https://littleminions.link): -data processing tools and algorithms -measuring tools -digital documentation tools -GIS plugins -hands-on digital inventions (e.g. for excavations) -data-driven tools (e.g. Linked Data, CSV, Big Data) After previous years (pt. I CAA 2018 Tübingen, pt. II CAA 2019 Krakow, pt. III CAA 2021 Limassol/virtual, pt. IV CAA 2022 Oxford/hybrid) spontaneous success of “Stand-up-Science”, you will also have the opportunity to spontaneously participate and demonstrate what you have on your stick or laptop. If you want to participate without an abstract in the spontaneous section of the session, don’t hesitate. Please come and spontaneously introduce your little minion! The minion session is designed for interested researchers of all domains who want to present their small minions with 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 normal talks, but take important and extensive steps in our research, a home. As an outcome of the session, we try to give support, that all presented tools and links to code repositories will be available for the research community on our website https://littleminions.link.
 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
S04. “Hey Google, stop that looter”: digital technologies against cultural heritage crimes; critical approaches, ongoing solutions and beyond
Arianna Traviglia, Center for Cultural Heritage Technologies – Istituto Italiano di Tecnologia
Michela De Bernardin, Center for Cultural Heritage Technologies – Istituto Italiano di Tecnologia
Riccardo Giovanelli, Ca’ Foscari University of Venice and Center for Cultural Heritage Technologies – Istituto Italiano di Tecnologia
Session type: Standard
Countering the devastation of archaeological sites caused by illegal excavations or voluntary destruction is at the forefront of worldwide governments agendas, but also cultural institutions and caring citizens are deeply concerned by this disruptive phenomenon. Looting (i.e., the unlawful removal of ancient artefacts conducted through non-scientific methods by robbers) is an old practice, dating back to ancient times. Recent events such as the 2004 Iraqi war, the 2011 ‘Arab Spring’, ISIS’s actions in the Middle East and North Africa, the COVID pandemic and the 2022 Ukraine war, determined a spiralling increase in looted items being available on the international antiquities market, both the legal and illegal ones. The last decade witnessed a growth in computer-aided technologies designed to monitor both looting activities and art markets, tools that have proven to be highly instrumental in halting/detecting unlawful behaviours. Remote sensing is being used to detect and monitor illicit excavations (Tapete and Cigna 2021) using multispectral imagery – investigated through both manual (Casana and Panahipour 2014; Contreras 2010; Stone 2008) and automatic recognition of looting patterns (Lasaponara and Masini 2021) –, SAR data (Tapete, Cigna and Donoghue 2016; El Haji 2021) and Multi-Temporal Analysis (Agapiou 2020). VHR imagery time-series deployed by Google Earth makes it now possible to locate several looted sites throughout the globe (Contreras and Brodie 2011; Parcak et al. 2016; Zerbini and Fradley 2018), opening avenues for the development of new methods of recognition. The potential of computer vision and machine learning methods applied to web-scraped content (Huffer and Graham 2018; Huffer, Wood and Graham 2019; Graham et al. 2020) is being investigated to track illicit on-line sales. Network Sciences derived methodologies have been studied to identify criminal networks of the antiquities trade (Tsiriogiannis and Tsiriogiannis 2016) and its actors within the so-called “grey market” of antiquities (Bowman 2008; Mackenzie 2019; Mackenzie and Yates 2016). Artificial Intelligence approaches are being developed to identify looted/robbed archaeological items appearing in the market (Winterbottom, Leone and Al Moubayed 2022). The monitoring, both manual and automatic, of Social Media, on-line forums and marketplace, as well as the deep web, is enabling to gather crucial information about the illicit market using both quantitative and content data (Al-Azm and Paul 2019; Hardy 2014, 2015, 2017, 2018; Paul 2018; Giovanelli 2018; Altaweel and Hadjitofi 2020; De Bernardin 2021). Databases of stolen objects and due diligence activities have been developed by enforcement units, such as the Comando Tutela Patrimonio Culturale in Italy and INTERPOL (Arma dei Carabinieri 2016). 3D imagery-fed blockchain technologies (Gandolfi and Cox 2018) are currently being investigated. The progresses of research in this domain are fast-paced and pushed by the increasing loss of archaeological contexts and Cultural Heritage items. The developed technologies are getting more specialized; however, they are often unable to achieve levels of sophistication that can concretely contribute to the fight against illicit trafficking. This session invites the submission of original papers in the areas outlined above (i.e. remote sensing, network sciences, computer vision, machine learning, data-mining, blockchain, qualitative and quantitative SM data analysis) and beyond that engage in a critical discussion on the approaches, solutions and outcomes of established and emerging technologies, in order to highlight the pros and cons of technological applications and to identify successful means and methods to concretely build systems able to fight and prevent the looting and the illicit trade of cultural heritage objects. We are also interested in new methods and applications that have not been fully explored yet in the domain of countering cultural property trafficking, but which should be taken into consideration for future developments, such as in the field of Network Sciences and Graph Theory. The session is mainly intended for researchers working in the broad domain of antiquities crimes using traditional and computational approaches; it also benefits those working in the described technologies and methods (remote sensing, machine learning etc.) in the broader context. The session is organized within the framework of the HORIZON EU RITHMS (Research, Intelligence and Technology for Heritage and Market Security) project, which aims to create an innovative, interoperable, and multifunctional Social Network Analysis (SNA) digital Platform able to identify criminal organised networks involved in trafficking of cultural property, thus providing investigators with valuable intelligence about the activities and evolution of those networks to support the prevention of future criminal offences.
Al-Azm, A and Paul, K A 2019 Facebook’s Black Market in Antiquities. Trafficking, terrorism, and war crimes. (June). Agapiou A 2020 Detecting Looting Activity through Earth Observation Multi-Temporal Analysis over the Archaeological Site of Apamea (Syria) during 2011-2012, Journal of Computer Applications in Archaeology, 3(1): 219-237. DOI: https://doi.org/10.5334/jcaa.56/
Altaweel, M and Hadjitofi, T A 2020 The sale of heritage on eBay: Market trends and cultural value, Big Data & Society, 7(2). DOI: https://doi.org/10.1177/2053951720968865. Arma dei Carabinieri 2016 PSYCHE : THE PROTECTION SYSTEM FOR CULTURAL HERITAGE HOME/2011/ISEC/AG/PRUM/4000002157. 2016. Available at http://tpcweb.carabinieri.it/SitoPubblico/psyche/generic.
Bowman, B A 2008 Transnational Crimes Against culture: Looting at Archaeological Sites and the ‘Grey’ Market in Antiquities, Journal of Contemporary Criminal Justice, 24(3): 225–242. DOI: https://doi.org/10.1177/1043986208318210.
Casana, J and Panahipour, M 2014 Satellite-Based Monitoring of Looting and Damage to Archaeological Sites in Syria, Journal of Eastern Mediterranean Archaeology and Heritage Studies, 2(2): 128–151. Contreras, D A 2010 Huaqueros and remote sensing imagery: assessing looting damage in the Viru Valley. Peru., Antiquity, 84(324): 544–545.
Contreras, D A and Brodie, N 2011 The Utility of Publicly-Available Satellite Imagery for Investigating Looting of Archaeological Sites in Jordan, Journal of Field Archaeology, 35(1): 101–114. DOI: https://doi.org/10.1179/009346910×12707320296838.
De Bernardin, M 2021 Palmyrene Funerary Portraits: a ‘Conflict Antiquities’ Case. In: Traviglia, A, Milano, L, Tonghini, C and Giovanelli, R (eds.) Stolen Heritage. Multidisciplinary Perspectives on Illicit Trafficking of Cultural Heritage in the EU and the MENA Region. Venice: Edizioni Ca’ Foscari, pp. 79-95. DOI: http://doi.org/10.30687/978-88-6969-517-9/004
El Hajj, H 2021 Interferometric SAR and Machine Learning Using Opens Source Data to Detect Archaeological Looting and Destruction, Journal of Computer Applications in Archaeology, 4(1): 47-62. DOI: https://doi.org/10.5334/jcaa.70/
Gandolfi, E and Cox, G 2018 New approaches to Open Data in Archaeology: the blockchain revolution. Paper presented to 2018 Computer Applications and Quantitative Methods in Archaeology (CAA) international conference, Tübingen, 19-23 March, 2018. Available at https://2018.caaconference.org/wp-content/uploads/sites/22/2018/03/AbstractBook.pdf [Last accessed 17 June 2019].
Graham, S, Lane, A, Huffer, D and Angourakis, A 2020 Towards a Method for Discerning Sources of Supply within the Human Remains Trade via Patterns of Visual Dissimilarity and Computer Vision, Journal of Computer Applications in Archaeology, 3(1): 253-268. DOI: https://doi.org/10.5334/jcaa.59/
Giovanelli, R 2018 Provenance non verificabili nel mercato di antichità romane: case study sui 300 oggetti di più alto valore in vendita in eBay US, Archeomafie, X: 115-135. Available at: http://hdl.handle.net/10278/3740198.
Hardy, S A 2014 Using Open-Source Data to Identify Participation in the Illicit Antiquities Trade: A Case Study on the Cypriot Civil War, European Journal on Criminal Policy and Research, 20(4): 459–474. DOI: https://doi.org/10.1007/s10610-014-9250-x.
Hardy, S A 2015 Is looting-to-order “just a myth”? Open-source analysis of theft-to-order of cultural property, Cogent Social Sciences, 1(1): 1–22. DOI: https://doi.org/10.1080/23311886.2015.1087110.
Hardy, S A 2017 Quantitative analysis of open-source data on metal detecting for cultural property: Estimation of the scale and intensity of metal detecting and the quantity of metal-detected cultural goods, Tong, S. (ed.) Cogent Social Sciences, 3(1): 1–49. DOI: https://doi.org/10.1080/23311886.2017.1298397.
Hardy, S A 2018 Metal-Detecting for Cultural Objects until ‘There Is Nothing Left’: The Potential and Limits of Digital Data, Netnographic Data and Market Data for Open-Source Analysis, Arts, 7(3): 40. DOI: https://doi.org/10.3390/arts7030040.
Huffer, D and Graham, S 2018 Fleshing Out the Bones : Studying the Human Remains Trade with Tensorflow and Inception, Journal of Computer Applications in Archaeology, 1(1): 55–63. DOI: https://doi.org/doi.org/10.5334/jcaa.8.
Huffer, D, Wood, C and Graham, S 2019 What the Machine Saw: some questions on the ethics of computer vision and machine learning to investigate human remains trafficking, Internet Archaeology, DOI: https://doi.org/10.11141/ia.52.5.
Lasaponara, R and Masini, N 2021 Remote and Close Range Sensing for the Automatic Identification and Characterization of Archaeological Looting. The Case of Peru, Journal of Computer Applications in Archaeology, 4(1): 126-144. DOI: https://doi.org/10.5334/jcaa.73/
Mackenzie, S 2019 White-Collar Crime, Organised Crime and the Challenges of Doing Research on Art Crime. In: Hufnagel, S. and Chappel, D. (eds.) The Palgrave Handbook on Art Crime. London: Palgrave Macmillan UK. pp. 839–853. DOI: https://doi.org/10.1057/978-1-137-54405-6_37.
Mackenzie, S and Yates, D 2016 Collectors on illicit collecting: Higher loyalties and other techniques of neutralization in the unlawful collecting of rare and precious orchids and antiquities, Theoretical Criminology, 20(3): 340–357. DOI: https://doi.org/10.1177/1362480615607625.
Parcak, S, Gathings, D, Childs, C, Mumford, G and Cline, E 2016 Satellite evidence of archaeological site looting in Egypt: 2002 – 2013, Antiquity, 90(349): 188–205. DOI: https://doi.org/10.15184/aqy.2016.1.
Paul, K 2018 Ancient Artifacts vs. Digital Artifacts: New Tools for Unmasking the Sale of Illicit Antiquities on the Dark Web, Arts, 7(2): 12. DOI: https://doi.org/10.3390/arts7020012. Stone, E C 2008 Patterns of looting in southern Iraq, Antiquity, 82(315): 125–138. DOI: https://doi.org/10.1017/s0003598x00096496.
Tapete, D, Cigna, F and Donoghue, D N M 2016 ‘ Looting marks ’ in space-borne SAR imagery: Measuring rates of archaeological looting in Apamea ( Syria ) with TerraSAR-X Staring Spotlight, Remote Sensing of Environment, 178(April): 42–58. DOI: https://doi.org/10.1016/j.rse.2016.02.055.
Tapete, D and Cigna, F 2021 Satellite Technologies for Monitoring Archaeological Sites. In: Traviglia, A, Milano, L, Tonghini, C and Giovanelli, R (eds.) Stolen Heritage. Multidisciplinary Perspectives on Illicit Trafficking of Cultural Heritage in the EU and the MENA Region. Venice: Edizioni Ca’ Foscari, pp. 155-167. DOI: http://doi.org/10.30687/978-88-6969-517-9/007.
Tsiriogiannis, C and Tsiriogiannis, C 2016 Uncovering the Hidden Routes: Algorithms for Identifying Paths and Missing Links in Trade Networks. In: Brughmans, T., Collar, A., and Coward, F. (eds.) The Connected Past Challenges to Network Studies in Archaeology and history. Oxford: Oxford University Press. pp. 103–122.
Winterbottom, T, Leone, A, Al Moubayed, N 2022 A deep learning approach to fight illicit trafficking of antiquities using artefact instance classification, Scientific Reports, 12, 13468. DOI: https://doi.org/10.1038/s41598-022-15965-2.
Zerbini, A and Fradley, M 2018 Higher Resolution Satellite Imagery of Israel and Palestine: Reassessing the Kyl-Bingaman Amendment, Space Policy, 44–45: 14–28. DOI: https://doi.org/10.1016/j.spacepol.2018.03.002.
S05. For new epistemologies in Archaeology: using probability, networks and mathematical models to build archaeological knowledge
Joel Santos, FCSH Nova Lisbon University
Daniel Carvalho, UNIARQ, LAQU, FCT
Session type: Standard
Investigating the complex nature of the human past is of paramount importance to archaeology. Throughout the years, several theoretical proposals on how to perceive the past have been constructed. From formulating law-like statements (Binford 1972; Schiffer 1976) to symbolic and contextual approaches (Hodder and Hudson 2003), passing to symmetrical and ontological critiques (Olsen 2013; Olsen and Witmore 2015), archaeological theory has experienced change and shifts in relative interest in the last several decades. However, a fundamental question arises: how are archaeologists able to face the near infinite possibilities that constitute the past? On top of this already difficult conundrum, the basis of our work is nothing but fragmented material remains, mere shadows of things that once were. Is this an impossible task?
We believe not. By applying methods and ideas with a strong mathematical basis, archaeologists can strive to reduce subjectivity and engage with a larger realm of questions. For example, the Bayesian approach used in Archaeology has increased in the last decades (Otarola-Castillo and Torquato, 2018; Otarola-Castillo, Torquato, and Buck, 2021), being applied in the most different areas, but is it possible to increase its application from chronological modeling using radiocarbon calibration (Buck et al., 1991; Price et al., 2021), bioarchaeology (Konigsberg et al., 1992; De Angelis et al., 2021), zooarchaeology (Fisher, 1987; Baumann et al., 2020), artifact analysis such as lithics or ceramics (Buck et al.,1996; Murray et al., 2020) or spatial analysis (Kirkinen, 1999; Wright et al., 2020) to archaeological theory and epistemology?
The objective of this session is to explore frameworks that are able to embrace a sheer volume of possibilities that shape complex events of the past, demonstrating how to build a sturdy epistemological basis. We intend to explore Bayesian methodology, Network Theory and AI theory and applications to discuss multiple ways for constructing hypotheses about the Past. With this premise in mind, we welcome papers that:
• Propose ways to build archaeological knowledge with methods from analytical and statistical backgrounds (e.g Mathematics, Computer Engineering);
• Embrace social, economical and political questions in archaeological contexts while dealing with great amounts of data;
• Using algorithms to construct hypotheses for archaeological endeavours;
• Explore novel paths in the creation of theoretical viewpoints, with Artificial Intelligence and Deep Learning.
Baumann, C., Wong, G.L., Starkovich, B.M. et al. (2020) – “The role of foxes in the Palaeolithic economies of the Swabian Jura (Germany)”. Archaeology Anthropology Science, 12: 208
Binford, L. R. (1972). An Archaeological Perspective. New York: Harcourt.
Buck C.E., Kenworthy J.B., Litton C.D., Smith A.F.M. (1991) – Combining archaeological and radiocarbon information: a Bayesian approach to calibration. Antiquity, 65, pp. 808–821
Buck C.E., Cavanagh W.G., Litton C.D. (1996) – Bayesian Approach to Interpreting Archaeological Data. West Sussex, UK: Wiley
De Angelis, F.D., Veltre,V., Varano,S., Romboni,M., Renzi,S., Zingale,S., Martínez-Labarga, C. (2020) – Dietary and Weaning Habits of the Roman Community of Quarto Cappello del Prete (Rome, 1st-3rd Century CE). Environmental Archaeology, pp. 1–15.
Fisher D.C. (1987) – Mastodont Procurement by Paleoindians of the Great Lakes Region:Hunting or Scavenging?. in: Nitecki M.H., Nitecki D.V. (eds) The Evolution of Human Hunting. Springer, Boston, MA.
Hodder, I. and S. Hudson (2003). Reading the Past. Current approaches in interpretation in archaeology. Cambridge: Cambridge University Press.
Kirkinen T. (1999) – GIS-assisted data analysis-finding meanings in complex spatial data sets. in New Techniques for Old Times. CAA98. Computer Applications and Quantitative Methods in Archaeology. Proceedings of the 26 th Conference, Barcelona, March 1998, ed. JA Barceló, I. Briz, A. Vila, pp. 255–258. Oxford, UK: Archaeopress
Konigsberg L.W., Frankenberg S.R. (1992) – Estimation of age structure in anthropological demography. American Journal of Physical Anthropology, 89, pp.235-256
Murray, J.K., Harris, J.A., Oestmo, S., Martin, M., Marean, C.W. (2020) – A new approach to identify heat treated silcrete near Pinnacle Point, South Africa using 3D microscopy and Bayesian modelling. Journal of Archaeological Science, 34: 102622
Olsen, B. (2013). In Defense of Things. Archaeology and the Ontology of Objects. Plymouth: Altamira Press.
Olsen, B. and C. Witmore (2015). Archaeology, symmetry, and the ontology of things: A response to critics. Archaeological Dialogues, 22(2): 187-97.
Otaróla-Castillo, E., Torquato, M.G. (2018) – “Bayesian Statistics in Archaeology”. Annual Review of Anthropology, 47, pp.435-453
Otaróla-Castillo, E., Torquato, M.G., Buck, C.E. (2021) – “The Bayesian Inferential Paradigm in Archaeology”. Manuscript accepted to the Handbook of Archaeological Sciences, 2 nd ed. Forthcoming volume under contract (2022). Edited by M.Pollard, R.A. Armitage and C.M. Makarewicz. Wiley
Price, M. H., Capriles, J. M., Hoggarth, J.A., Bocinsky, R.K., Ebert, C.E., Jones, J. H. (2021) – End- to-end Bayesian analysis for summarizing sets of radiocarbon dates. Journal of Archaeological Science, 135, 105473
Schiffer, M. (1976). Behavioral Archaeology. New York: Academic Press.
Wright, D.K., Kim, J., Park, J., Yang, J., Kim, J. (2020) – Spatial modeling of archaeological site locations based on summed probability distributions and hot-spot analyses: A case study from the Three Kingdoms Period, Korea. Journal of Archaeological Science, 113, 105036.
S06. Stay connected: Developing Mobile GIS for team-based collaboration in archaeological research
Julia M. Chyla, University of Warsaw. Faculty of Archaeology
SOBOTKOVA, Adéla, Aarhus University, School of Culture and Society,
BUŁAWKA, Nazarij, Landscape Archaeology Research Group (GIAP), Catalan Institute of Classical Archaeology
CIRIGLIANO, Giuseppe Prospero, University of Siena, Department of History and Cultural Heritage
Session type: other (10-15 min papers + moderated discussion afterwards)
Mobile GIS Special Interest Group has in its previous CAA conference editions (2017, 2018, 2019, 2021) drawn attention to the importance of mobile GIS in archaeological and other field research, specifically its impact and contribution to fieldwork methodology and data collection (Buławka and Chyla, 2020; Sobotkova et al., 2021). In this edition, we survey how the use of mobile GIS in archaeology has progressed in recent years. In the early phase of COVID pandemic, Scerri et al. argued that sciences working in the field, including archaeology, had to change their ways (2021). The review of the recently published literature partly confirms it. As most international expeditions were canceled, scholars working in the field had to stop their projects. Many projects abandoned field work in favor of office work, for example remote sensing and data analysis. Others, in the late phase of the pandemic, found their way to continue working by novel methods of collaboration (Geser 2021; Magnani et al. 2021; Matte and Ulm 2021). COVID demonstrated the benefit of producing FAIR digital data in the field. Robust toolkit ensured that the collected data were born-digital, complete and consistent upon departure from fieldwork. Having all data shared and accessible by all team-members afterwards meant that work could continue remotely, which was a source of relief during the lockdown (Sobotkova et al., 2021). Additionally, we would like to explore the current differences in collaborative solutions between open-source and commercial software. Do the different OS and commercial software entail a different organization of archaeological fieldwork? What aspects and reasons lead a research team to choose an OS versus a commercial software? What is the range of funding models used to develop or deploy different mobile data capture applications? How should archaeologists prepare for OS updates, changes in hardware compatibility or application funding models so as to retain the ability to use the same workflow in the future? Another aspect that we would like to address at CAA 2023 is the capability to produce standardized results that follow good practice using mobile GIS nowadays. Some archaeologists report increased fieldwork efficiency thanks to the use of mobile devices (Austin 2014; Ames et al. 2020) while others focus on the downsides of the digital medium, such as deskilling, (Caraher 2016; Gordon et al. 2016), or stress the need to manage workplace change and fine-tune daily operation under the new circumstances (Vanvalkenburgh 2018). What makes the difference? Have the mobile devices transformed the entire lifecycle of archaeological research from team-based field data capture to analysis, sharing, and publishing, or affected only the day-to-day working processes in the field? And more specifically: is mobile GIS essential for digital fieldwork? If so, what are the must-have features of mobile GIS and how do you prioritize them? The session invites papers that may concern methodological and technical aspects and will be finished with a moderated discussion.
Ames, Christopher J. H., Matthew Shaw, Corey A. O’Driscoll, and Alex Mackay. 2020. “A Multi-User Mobile GIS Solution for Documenting Large Surface Scatters: An Example from the Doring River, South Africa.” Journal of Field Archaeology 45 (6): 394–412. https://doi.org/10.1080/00934690.2020.1753321.
Austin, Anne 2014. ‘Mobilizing Archaeologists: Increasing the Quantity and Quality of Data Collected in the Field with Mobile Technology’, Advances in Archaeological Practice, 1, 12-23.
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.
Scerri, Eleanor M. L., Denise Kühnert, James Blinkhorn, Huw S. Groucutt, Patrick Roberts, Kathleen Nicoll, Andrea Zerboni, et al. 2020. “Field-Based Sciences Must Transform in Response to COVID-19.” Nature Ecology & Evolution 4 (12): 1571–74. https://doi.org/10.1038/s41559-020-01317-8.
Caraher, William. 2016. “Slow Archaeology: Technology, Efficiency, and Archaeological Work.” In Mobilizing the Past for a Digital Future; the Potential of Digital Archaeology, edited by Erin Walcek Averett, Jody Michael Gordon, and Derek B. Counts, 421–42. The Digital Press @ University of North Dakota. http://dc.uwm.edu/arthist_mobilizingthepast/18.
Geser, Guntram. 2021 “Impact of COVID-19 on Archaeology and Cultural Heritage.” Salzburg. https://ariadne-infrastructure.eu/wp-content/uploads/2021/11/COVID-19_impact-archaeology-and-cultural-heritage_29Oct2021.pdf.
Gordon, Jody Michael, Erin Walcek Averett, and Derek B. Counts. 2016. “Mobile Computing in Archaeology: Exploring and Interpreting Current Practices.” In Mobilizing the Past for a Digital Future; the Potential of Digital Archaeology, edited by Erin Walcek Averett, Jody Michael Gordon, and Derek B. Counts, 1–32. The Digital Press @ University of North Dakota. http://dc.uwm.edu/arthist_mobilizingthepast/2.
Magnani, Matthew, Natalia Magnani, Anatolijs Venovcevs, and Stein Farstadvoll. 2022. “A Contemporary Archaeology of Pandemic.” Journal of Social Archaeology 22 (1): 48–81. https://doi.org/10.1177/14696053211043430.
Mate, Geraldine, and Sean Ulm. 2021. “Working in Archaeology in a Changing World: Australian Archaeology at the Beginning of the COVID-19 Pandemic.” Australian Archaeology 87 (3): 229–50. https://doi.org/10.1080/03122417.2021.1986651.
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.
VanValkenburgh, Parker, Luiza O. G. Silva, Chiara Repetti-Ludlow, Jake Gardner, Jackson Crook, and Brian Ballsun-Stanton. 2018. “Mobilization as Mediation.” Advances in Archaeological Practice. https://doi.org/10.1017/aap.2018.12.
S07. Open Analytical Workflows and Quantitative Data Integration in Archaeological Prospection
Karsten Lambers, Leiden University (NL – Dept. of Archaeological Sciences, Faculty of Archaeology)
Jitte Waagen – University of Amsterdam (NL – Faculty of Humanities)
Philippe De Smedt – Ghent University (BE – Faculty of Bioscience Engineering; Faculty of Arts and Philosophy)
Martijn van Leusen – University of Groningen (NL – Faculty of Arts, Groningen Institute of Archaeology)
Session type: Standard
This session invites contributions from the field of prospective archaeology that address the design of open, reproducible, and transferable workflows for archaeological and environmental data processing, analysis and interpretation and/or quantitative data integration across different sensors, modalities and scales for the study or archaeological landscapes.
In recent years, archaeological prospection has benefited enormously from the increasing quantity, quality and availability of digital data from remote sensing and geophysics that record selected environmental parameters across space, often at high resolution. This wealth of data now allows archaeologists to go beyond the traditional remit of archaeological prospection, namely the detection and mapping of traces of past human activity, and to study landscapes and the ecological and anthropogenic processes that formed them over time from a holistic perspective.
However, the full potential of this approach is often not realized in the practice of archaeological research and heritage management due to a limited availability of skills, tools and protocols. Many projects focus on specific data types or analytical methods, without making use of additional sources of information that would also be available and might be able to add important interpretative dimensions. Often, the choice of data and methods is motivated by practical constraints rather than analytical potential. Also, the joint analysis of remote sensing or geophysics data and data from field observations (e.g., surface survey, corings, excavations) is often performed on a qualitative level only, due to a lack of suitable protocols for a combined quantitative analysis.
Another common problem is that many projects create ad hoc solutions for their analytical and interpretative workflow that are not easily reproducible or transferable to other projects. There is still a lack of open, standardized protocols and workflows that can be applied to a variety of cases, even though promising approaches exist (e.g., Lozić & Štular 2021). Further inspiration may be drawn from other domains that often use the same environmental data, e.g. ecology, geomorphology or soil science. Here, the development of open analytical and interpretative workflows that allow the integration and joint quantitative analysis and interpretation of data from remote sensing and field observations is further advanced than in archaeology (see, for instance, Ghamisi et al. 2019; Chatterjee et at. 2021).
In this session, we welcome papers that showcase and evaluate novel approaches to analytical workflows and data integration in archaeological prospection. Alongside case-studies that offer concrete examples of these issues in archaeology and presentations of workflows and theoretical frameworks, we encourage contributions on best practices in associated fields and their relevance for archaeological applications.
Ghamisi, P.; Rasti, B.; Yokoya, N.; Wang, Q.; Hofle, B.; Bruzzone, L.; Bovolo, F. et al. 2019. Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art. IEEE Geoscience and Remote Sensing Magazine 7, 6–39. https://doi.org/10.1109/MGRS.2018.2890023.
Chatterjee, S.; Hartemink, A. E.; Triantafilis, J.; Desai, A. R.; Soldat, D.; Zhu, J.; Townsend, P.; Zhang, Y. and Huang, J. 2021. Characterization of Field-Scale Soil Variation Using a Stepwise Multi-Sensor Fusion Approach and a Cost-Benefit Analysis. CATENA 201, 105190. https://doi.org/10.1016/j.catena.2021.105190
Lozić , E.; Štular, B. 2021. Documentation of Archaeology-Specific Workflow for Airborne LiDAR Data Processing. Geosciences 11, 26. https://doi.org/10.3390/geosciences11010026
S08. Where do you draw your lines? Mapping transformation of archaeological practice in the digital age
Nicolò Dell’Unto, Lund University
James Stuart Taylor, University of York
Session type: Standard
Archaeology has always had a close relationship with emerging digital technologies, and the last ten years have seen a dramatic uptick in the application of these technologies across the discipline (‘The Digital Turn?’). From the refinement of database management systems, ontologies, and the principles that guide them (F.A.I.R.), to experimentation with computational approaches like Network Analysis and Agent Based Modelling, to the almost universal adoption of spatial technologies and the current golden age of 3D data acquisition and VR. From our perspective, the impact upon our fieldwork has been profound. The question of where you draw your lines has a literal gravitas these days (on paper, in a GIS, in your simulation, or straight into your 3D environment?). But what about the discipline more broadly? We have recently argued that digital practice that consumes emergent technologies often emulates an analogue counterpart as a skeuomorph of practice, as part of a process of testing the affordances and limitations of new technologies. In doing so, these technologies are socialised as we become comfortable with them, so that we can ultimately use them to transform our practice (Taylor & Dell’Unto 2021). Increasingly these transformations may be more fluid, with archaeologists potentially shifting their practice from analogue to digital, digital to digital, and even digital to analogue. In this session, we would like to explore these transformations, no matter how great or small; where do you draw the line? [~your lines?]. How has your archaeological practice been affected by new and emergent technologies? In the field? In the lab? In the museum? And across the years? We invite you to literally map or diagram these transformations, reflect upon them in the example of your own practice and together, perhaps we will explore emerging digital trends and future disciplinary directions. Session Structure This will be a standard session focused upon a series of 20-minute papers in which we literally encourage you to ‘map’, ‘chart’ or visualise your transformative practice. We encourage collaborative papers that include or foreground the work of junior researchers. The last part of the session will be set aside for a round table discussion of some of the themes that emerge throughout the day.
Taylor, J., & Dell’Unto, N. (2021). Skeuomorphism in digital archaeological practice: A barrier to progress, or a vital cog in the wheels of change? Open Archaeology, 7(1), 482-498. https://doi.org/10.1515/opar-2020-0145
S09. Digital approaches to Roman port urbanism: from data acquisition to computational analysis and visual reconstruction
Stéphanie Mailleur, Postdoctoral researcher MAP-Aria (UMR 3495 CNRS-Ministère de la Culture)
Adeline Hoffelinck, BAEF Postdoctoral Fellow at Harvard Classics Department, Postdoctoral researcher Ghent University
Session type: Standard
Under the Roman Empire, ports were nodal points, significant hubs of economic – and cultural – interaction and movement, where ships, people and goods both departed and arrived. The ports’ urban infrastructure and organization facilitated smooth import and export of goods and, as such, ensured connectivity in the entire network. We can, therefore, say that ports were the heart and motor of maritime exchange networks.
While studying the interaction between these nodal points (often represented as dots on a map) remains of high importance – to detect patterns of trade/connectivity and evaluate organizational aspects related to maritime trade – we want to shift the focus in this session to the dots themselves: the ports. Although the study of port environments has increased substantially in the last few years due to the development of disciplines such as underwater and maritime archaeology, the topic of port urbanism – addressing the port’s unique urban fabric, its structure and infrastructure – often remains underexplored. This session aims to examine both the port’s configuration towards the sea and its urbanization away from the sea through digital and computational methodologies.
The port’s urban arrangement on the waterfront – thus the purely functional infrastructure and facilities – guaranteed (long distance) trade and the logistical aspects of loading and unloading of goods, as well as their control (quality and weight) and storage. But ports were not only transit hubs, ‘dots’ of arrival and departure, they were places of residence, places of vibrant urban and cultural life developing away from the seafront. The merging of these two types of urbanism ensured that ports formed a real urban landscape ‘with enough features of complete towns to give it an acceptably urban aspect’ (MacDonald 1988, 262).
In this session, we want to evaluate how digital and computational approaches and methods can be used to reach new perspectives on the urbanism of Roman ports. We aim to approach this topic from a variety of angles, with papers (20 min + 10 min discussion) particularly – but not exclusively – addressing the following main questions:
- How did ports facilitate movement/interaction of people and goods within the port itself?
- How was the urbanization towards and away from the sea connected and how did this evolve? In other words, how was the city and its port connected?
- How did the port’s urban texture impact maritime activities, and vice versa, how did these activities influence the urban structure of the port?
- How did the urban organization of ports facilitate and ensure maritime trade connections?
We invite submissions of different applicative digital approaches for modeling or simulating Roman port cities whose results come from either invasive (excavations) or non-invasive research (drone, aerial or geophysical surveys). Possible topics include but are not limited to applications or discussions of the following approaches:
- Topographic modeling
- GIS modeling and simulations
- Computational analysis of spatial configuration of port cities, through for instance urban network analysis, space syntax analysis, etc.
- 3D reconstruction methods
- Cultural mediation tools like AR and VR
Keay, S., Campbell, P., Crawford, K., Moreno Escobar, M., 2021. Space, Accessibility and Movement through the Portus Romae. In: Vermeulen, F., Zuiderhoek, A., Space, Movement and the Economy in Roman Cities in Italy and beyond. Routledge. London & New York. pp. 375-417.
Leidwanger J., 2020. Roman Seas. A Maritime Archaeology of Eastern Mediterranean Economies, Oxford University Press: Oxford.
Leidwanger J., Knappett C., 2018. Maritime Networks in the Ancient Mediterranean World, Cambridge University Press: Cambridge.
MacDonald W., 1988. The Architecture of the Roman Empire: an Urban Appraisal, Yale University Press: Yale.
Mailleur, S., Saleri, R., 2022 (forthcoming). Restituer la morphologie des villes portuaires antiques : de l’image 2D à la 3D, in: SCAN’22, 10e Séminaire de Conception Architecturale Numérique, Lyon, oct. 2022.
Moreno Escobar, M., 2021. Roman ports in the lower Tiber valley: computational approaches to reassess Rome’s port system. Papers of the British School at Rome. pp. 1-30.
Saleri, R., « Digital Generative Tools for Restitution and Mediation for Cultural Heritage », in Proceedings of EVA (Electronic Visualisation and the Arts, London: BCS Learning & Development, 2019), https://doi.org/10.14236/ewic/EVA2019.2
Westerdahl, C. 1992. “The maritime cultural landscape”, in: International Journal of Nautical Archaeology 21 1: 5–14.
S10. Computer applications in archaeology – Bringing South Asia together
Pallavee Gokhale, Senior Research Fellow, Humanities & Social Science, Indian Institute of Science Education and Research (IISER), Pune, India
Parth Chauhan – Assistant Professor, Humanities & Social Science, IISER Mohali, India
Ketika Garg – Postdoctoral Research Associate, California Institute of Technology, Pasadena, California, USA
Session type: Standard
South Asia (SA) is one of the archaeologically and historically rich geographies in the world. Though archaeology as a domain was initiated and had its founding years during the colonial period, the explorations, excavations, and material studies have reached new heights since then. Being the home of the Buddhist era, Harappan civilisation and several prehistoric phases, SA has brought forward interesting materials for analysis that are closely associated with (i)presence of hominins, (ii)early hunting-gathering communities, (iii)early domestication of plants and animals to (i)social systems, (ii)dynastic rules, (iii)urbanisation, (iv) diverse yet contemporary language and cultural systems and many more which assist in better understanding of multiple aspects of human past in this part of the globe.
In recent decades, the advent of technology and computer applications has touched almost all aspects of life, and archaeology is not an exception at all. In SA, many examples of employing these technologies can be seen: geospatial technologies and GPR surveys to name examples. Analysing quantitative data for ceramics, stone-tools, coins, etc is another discourse as well as 3D modelling of monuments and artefacts for academic studies, museum displays and public education. Furthermore, the use of agent-based modeling to simulate prehistoric environments and human behaviour can be used to shed light on early mobility patterns and socio-cultural systems.
What is interesting in SA, especially India, is that many of these listed examples continue to remain as examples or case-studies but are yet to become main-stream practice or part of the curriculum. Likewise, basic technologies for storing data in structured databases, documenting surveys or explorations using appropriate coordinate systems and formats is yet to become standardised in SA archaeology. It is currently taught, studied, and perceived mostly as a humanities and social science (HSS) subject and has not yet been fully explored for computational research.
Computer applications (CA) help bring data together from several domains, transform it, visualise it and analyse in ways which are otherwise humanly impossible. Recognising its value, ensuring academic training, and implementing standard practices is the need of the time in Indian archaeology. CA should not be seen as one of the outcomes or characteristics of processual archaeology but rather a starting point for pursuing any theoretical approach.
This session aims to bring together scholars from SA who have innovative ways of employing CAs at any stage of archaeological research work. We invite talk abstracts from enthusiastic scholars from diverse academic backgrounds wishing to take archaeological research in SA to the next level by applying computational and theoretical tools to shed light on the rich history of SA. Those who wish to present their ideas for tackling specific problems such as academic divide, lack of training, research bias, budgetary constraints, and historical baggage (to name a few examples) are also more than welcome to submit abstracts.
S11. The Age of #Archaeogaming: The Past and Future of Archaeology + Video Games
Aris Politopoulos, Leiden University & VALUE Foundation
Sebastian Hageneuer, University of Cologne
Csilla E. Ariese, VALUE Foundation & Reinwardt Academy
Session type: Standard
The last decade has seen the exciting development of a new field in digital archaeology: archaeology and video games. The field, commonly known as archaeogaming, deals with such concepts as the use of video games for archaeological research, the archaeological study of video games, and the implementation of video games for heritage and outreach. Popularised initially on social media and in blogs, #Archaeogaming has brought together researchers from diverse disciplinary backgrounds. In this session we will celebrate the origins of the field, consider its current inter- and intra-disciplinary synergies, and dream together to envision its futures. ORIGINS The engagement of archaeologists with video games has no singular point of origin, neither in time nor in place. Although archaeologists have used computer applications for half a century, and the first historical video game dates to the era of the earliest computer games, Archaeogaming as a field of study is significantly younger. The first publications on the topic appeared in the 2000s, dealing with a variety of topics, from exploratory (Gardner 2007), to experimental (Morgan 2009), to heritage (Champion 2011). It was in the early 2010s however, when the term ‘archaeogaming’ was coined, after the namesake blog by Andrew Reinhard, and the field started taking shape. The origins of the field were characterised by a great freedom of exploration. In part, this was due to the fact that the new area of study had no set boundaries, nor any clear research agenda (Mol et al. 2021). Additionally, significant research was carried out outside of formal academic settings, by researchers in their own free time or at least on the side lines of grant projects. This freedom enabled a wide-spread exploration of all aspects and angles of Archaeogaming and also drew people from different disciplines and, notably, many early career scientists. Entering #Archaeogaming’s second decade, we are ready to reflect on our origins. What qualities characterise the field and set it apart from other research strands in computational archaeology? Which milestones, perhaps outside the Anglophone, should be included in its origin story? We welcome any papers that delve into the (brief as it may be) history of #Archaeogaming. INTER-/INTRA- DISCIPLINARY SYNERGIES Over the years, the field’s popularity has drawn increasingly more participants, especially appealing to those whose gaming at home has taken on extra meaning. With openness and innovation at its core, there seems to be no end to the themes and potential avenues for research. Archaeogaming studies have included a wide variety of topics like decolonizing and ethical movements, collaborative digital survey projects, and game making experiments. The fluidity of the field has allowed for a richness of synergies that fearlessly cross disciplinary and sub-disciplinary boundaries. Despite archaeogaming’s growth and the enthusiasm of its participants, the field has struggled to gain a secure foothold in academia. With play as a core component of its practice, archaeogaming has often been disregarded as frivolous or non-serious. While universities have been quick to showcase archaeogaming endeavours to attract new students, they have been slow to formalise archaeogaming in terms of funding, teaching positions, or long-term support. As a result, archaeogaming projects have mostly been incidental and there is a lack of sustainability. Conferences and an exponential increase in academic publications have helped to formalise archaeogaming as a ‘real’ or ‘legitimate’ strand of research, but this struggle for understanding has taken time and effort away from further expanding the field. Where does archaeogaming stand at the beginning of its second decade? What is the actuality of its practice – and is this what the field should indeed be focusing on? We welcome papers that reflect on the current state of the field of Archaeogaming and any areas that remain un- or under-explored. We also welcome presentations about ongoing or recent Archaeogaming projects, particularly those discussing current methods and practices. ENVISIONING THE FUTURE Although not a completely blank slate anymore, the future of archaeogaming is still malleable and open. From our perspective, we expect three major influences on how this future will take shape. Fundamentally, the future of video games and the video game industry, including technological developments such as AR and VR, will significantly impact the source materials that we can work and play with. Secondly, we anticipate that established and new scholars will build upon previous research: celebrating past achievements while also correcting our course to compensate for omissions, gaps, and weaknesses. Finally, Archaeogaming’s future will also be dependent on structural and institutional support both from within academia as well as the game development industry. In this session we would like to welcome all archaeogaming scholars, enthusiasts, or people curious about the field to envision its future together. We are curious to hear about new avenues to explore, but equally interested in how tried and tested methods can be applied to future games. Please share your dreams or future realities. PAST AND FUTURE This session is both about celebrating archaeogaming’s origins and about envisioning the exciting opportunities that lie ahead. We welcome students and scholars whether you are new to the field or have been following and contributing over the years. We welcome traditional paper presentations as well as playful projects and game demonstrations.
Champion, E. 2011. Playing with the Past. London: Springer. Gardner, A. 2007. Playing with the Past: A Review of Three ‘Archaeological’ PC Games. European Journal of Archaeology 10(1), 74-77.
Mol, A.A.A., A. Politopoulos, C.E. Ariese, B. van den Hout and K.H.J. Boom, 2021. Introduction. In C.E. Ariese, K.H.J. Boom, B. van den Hout, A.A.A. Mol and A. Politopoulos (eds), Return to the Interactive Past: The Interplay of Video Games and Histories (7-18). Leiden: Sidestone Press.
Morgan, C. 2009. Re-building Çatalhöyük: Changing Virtual Reality in Archaeology. Archaeologies: Journal of the World Archaeological Congress 5(3), 468-487.
S12. Chronological modelling: formal methods and research software
Eythan Levy, University of Bern, Department of Jewish Studies
Thomas Huet, University of Oxford, School of Archaeology
Florian Thiery, Römisch-Germanisches Zentralmuseum, Department of Scientific IT
Allard W. Mees, Römisch-Germanisches Zentralmuseum, Department of Scientific IT
Session type: Standard
Time and its analysis are at the heart of archaeology: one of the main objectives of the archaeologist is the establishment of a temporal framework for a given layer, site or material culture. But archaeology covers such a wide range of cultures, dispersed both in time and space, that contextual chronological assessments are constructed using very different tools, languages and techniques. It creates as many different temporal and cultural frameworks as there are specialties, with notable differences in approaches depending on whether one is dealing with absolute or relative chronology, laboratory techniques or cultural approaches, deterministic or statistical methods (Buck and Millard 2004). The aim of this session is to explore a wide variety of research tools and techniques related to (semantic) chronological modelling in archaeology in order to identify common methodological frameworks and to build bridges between specialties. This also invites approaches from CAA Special Interest Groups (SIG), e.g. on Scientific Scripting Languages in Archaeology (SSLA) and Semantics and LOUD in Archaeology (Data Dragon) as well as from the CAA Little Minions on chronological modelling. These SIGs are following the FAIR (Bahin et al. 2020) and FAIR4RS (Hong et al. 2022) principles in the idea of Open Science, including Open Access, Open (Research) Data and Open Source (Research) Software.
We invite papers in all fields related to time/chronology research, including:
Bayesian modelling. Bayesian modelling has revolutionized the way radiocarbon dating is practised nowadays (Buck et al. 1991; Bronk Ramsey 2009). The introduction of known priors (e.g., stratigraphic sequences, termini post/ante quem) into the radiocarbon calibration process enables researchers to obtain much more precise dating intervals than previously, when radiocarbon samples were individually calibrated rather than incorporated into a model. Many software tools are currently available for Bayesian modelling in archaeology, such as OxCal, BCal, ChronoModel, as well as R and Python packages.
Stratigraphic modelling. The most famous tool for stratigraphic modelling is the Harris matrix (Harris 1989), which has been the focus of much software development (Harris Matrix Composer, Stratify, Stratifiant, …). Originally designed as a tool restricted to relative chronology, the Harris matrix has also seen developments aimed at extending this formalism to include absolute dating elements (see for example Desachy 2016). Similar efforts have extended the model’s power to be able to automatically detect temporal relations between stratigraphic units (see for example the Phaser tool).
Temporal logics. Temporal logics is an important field of mathematical and computer science research (Demri et al. 2016), which has up to now found too little applications in archaeological research, probably due to a lack of communication between the relevant research communities. The main results of temporal logics widely applied and cited by archaeologists (see for example Holst 2004; May 2020) are the fundamental, but old, Allen relations (Allen 1984, 1991). The archaeological research community has otherwise only brought too little attention to recent research results in temporal logics.
Seriation techniques. A classical way to provide relative chronology between artifacts, even in the absence of stratigraphic information, is seriation (O’Brien and Lyman 1999). In its variant called frequency seriation, the relative frequencies of each type of artifacts found within the same layer are computed and presented in chart form. The relative order between these layers (possibly coming from different sites, thus not featuring a relative stratigraphic order with each other) can then be established using the hypothesis of unimodality of artifact production. Seriation is an old but powerful method, which seems to have fallen out of fashion in many fields of Old World archaeology, but that still saw significant advances in the last decades (see for example Lipo, Madsen and Dunnell 2015).
Chronological networks. Until recently, little attention had been brought to the application of deterministic (i.e. non-statistical) techniques to building wide regional chronologies, based on historical data and cultural synchronisms. The goal of such techniques is to automate the archaeological cross-dating process by encoding a network of chronological relationships between temporal entities, and using algorithms to build the global chronology by propagating along the network a set of absolute dates located at specific nodes of the network. This approach has recently been implemented by two software tools: Groundhog (Falk 2016, 2017, 2020) and ChronoLog (Levy et al. 2021a, 2021b), relying on different techniques (exhaustive search and graph-theoretic techniques, respectively).
Linked Open Time Data (LOTD). Chronological Linked Open Data provides chronological space-time-gazetteers, e.g. PeriodO, GODOT and ChronOntology, and standard formats and ontologies, e.g. RDF, OWL TIME, EDTF, and CIDOC CRM, Alligator Ontology, AMT Time Ontology. LOTD and open source research tools allow for reproducible research, the unveiling of “hidden assumptions” in archaeological data and the semantic modelling of fuzziness and wobbliness. An example could be statistical approaches such as the horseshoe paradigm using correspondence analysis and the application of temporal logics to do temporal reasoning (Madsen 1998; Thiery and Mees 2018).
Other approaches. A host of other formal approaches to chronological modelling and computation have been explored in the recent years, such as fuzzy logics (Niccolucci and Hermon 2015), aoristic analysis (Crema 2012), and evidence density estimation (Demján and Dreslerová 2016).
We welcome papers dealing with new theoretical, methodological and research software developments in any of the above fields, in order to promote shared practices and the discovery of new ideas and paradigms.
Allen, J.F. 1984. Towards a general theory of action and time. Artificial Intelligence 23: 123–154.
Allen, J.F. 1991. Time and time again: the many ways to represent time. International Journal of Intelligent Systems 6(4): 341–355.
Bahim, C., Casorrán-Amilburu, C., Dekkers, M., Herczog, E., Loozen, N., Repanas, K., Russell, K. and Stall, S., 2020. The FAIR Data Maturity Model: An Approach to Harmonise FAIR Assessments. Data Science Journal 19(1): 41. DOI: http://doi.org/10.5334/dsj-2020-041
Bronk Ramsey, C. 2009. Bayesian analysis of radiocarbon dates. Radiocarbon 51: 337–360.
Buck, C.E., Kenworthy, J.B., Litton, C.D. and Smith, A.F.M. 1991. Combining archaeological and radiocarbon information: a Bayesian approach to calibration. Antiquity 65: 808–21.
Buck, C.E. and Millard, A. 2004. Tools for Constructing Chronologies: Crossing Disciplinary Boundaries. London.
Chue Hong, N. P., Katz, D. S., Barker, M., Lamprecht, A-L, Martinez, C., Psomopoulos, F. E., Harrow, J., Castro, L. J., Gruenpeter, M., Martinez, P. A., Honeyman, T., et al. (2022). FAIR Principles for Research Software version 1.0. (FAIR4RS Principles v1.0). Research Data Alliance. DOI: https://doi.org/10.15497/RDA00068
Crema, E.R. 2012. Modelling temporal uncertainty in archaeological analysis. Journal of Archaeological Methods and Theory 19: 440–461.
Demján, P. and Dreslerová, D. 2016. Modelling distribution of archaeological settlement evidence based on heterogeneous spatial and temporal data. Journal of Archaeological Science 69: 100–109.
Demri, S., Goranko, V. and Lange, M. 2016. Temporal Logics in Computer Science: Finite-State Systems (Cambridge Tracts in Theoretical Computer Science). Cambridge.
Desachy, B. 2016. From observed successions to quantified time: formalizing the basic steps of chronological reasoning. Acta Imeko 5: 4–13.
Falk, D.A. 2016. Groundhog: A Computer test laboratory to validate chronological hypotheses. Research poster presented at the 2016 Annual Meeting of the American Schools of Oriental Research (ASOR). http://www.groundhogchronology.com/poster.pdf (accessed 23/9/2021).
Falk, D.A. 2017. Evaluating chronological hypotheses by computer analysis in light of low and middle chronological frameworks. Abstract of a paper presented at the 2017 Annual Meeting of the American Schools of Oriental Research (ASOR). https://www.asor.org/wp-content/uploads/2019/01/ASOR-Program-2017.pdf (accessed 23/9/2021).
Falk, D.A. 2020. Computer analytics in chronology testing and its implications for the date of the Exodus. In: Averbeck, R.E., Younger Jr, K.L., eds. “An Excellent Fortress for His Armies, a Refuge for the People”, Egyptological, Archaeological, and Biblical Studies in Honor of James K. Hoffmeier. University Park, PA: 99–111.
Harris, E. 1989. Principles of Archaeological Stratigraphy (second edition). London.
Holst, M.K. 2004. Complicated relations and blind dating: formal analysis of relative chronological structures. In: Buck, C.E. and Millard, A.R., eds. Tools for Constructing Chronologies. London: 129–147.
Levy, E., Geeraerts, G., Pluquet, F., Piasetzky, E. and Fantalkin, A. 2021a. Chronological networks in archaeology: a formalised scheme. Journal of Archaeological Science 127: article 105225.
Levy, E., Piasetzky, E. and Fantalkin, A. 2021b. Archaeological cross dating: a formalized scheme. Archaeological and Anthropological Sciences 13: article 184.
Lipo, C.P., Madsen, M.E. and Dunnell, R.C. 2015. A Theoretically-Sufficient and Computationally- Practical Technique for Deterministic Frequency Seriation. PLoS ONE, 10(4): 1–31.
Madsen, T. 1988. Multivariate statistics and archaeology. In: Madsen, T. (ed.), Multivariate Archaeology. Numerical Approaches in Scandinavian Archaeology. Jutland Archaeological Society Publications 21, 7-28.
May, K. 2020. The Matrix: Connecting Time and Space in Archaeological Stratigraphic Records and Archives. Internet Archaeology 55. https://doi.org/10.11141/ia.55.8 (accessed 3/10/2021).
Niccolucci, F. and Hermon, S. 2015. Time, chronology and classification. In: Barcelo, J.A. and Bogdanovic, I., eds. Mathematics and Archaeology. Boca Raton: 257–271.
O’Brien, M.J. and Lyman, R. L. 1999. Seriation, stratigraphy, and index fossils: the backbone of archaeological dating. New York.
Thiery, F. and Mees, A. 2018. Taming the chronology of South Gaulish Samian found at Hadrian’s Wall and the German Limes using Linked Open Data, UK Chapter of Computer Applications and Quantitative Methods in Archaeology (CAA-UK 2018), Edinburgh, Scotland, 26th October 2018. DOI: 10.5281/zenodo.1469298.
S13. An inventory of the Sea: our shared marine heritage challenges and opportunities
Peter McKeague, Historic Environment Scotland
Professor Julian Richards, Archaeology Data Service, University of York
Dr Clare Postlethwaite, MEDIN Coordinator, National Oceanography Centre
The marine environment is a vast resource, covering over 70% of the Earth’s surface. Our seas provide an exceptional record of human activity from the seabed to the shore; from iconic wrecks through submerged landscapes and inter-tidal archaeology to the ports and harbours providing the onshore infrastructure supporting fishing and trade. Despite the richness of our marine heritage, accessing, re-using and presenting information about that heritage can be challenging – much more so than for terrestrial archaeology. Marine data are expensive to collect but have considerable reuse potential to increase our knowledge. The multi-disciplinary character of marine data, including commercially or scientifically sensitive data, pose particular challenges to ensuring that data conform to the FAIR Data principles (https://www.go-fair.org/fair-principles/). Of course, there is a large international dimension to marine and maritime data, with trading connections, ships logs and manifests adding rich detail to our understanding of maritime traffic. Our marine heritage is more than ships and wrecks. Intertidal archaeology offers opportunities for public engagement and citizen science but is particularly at threat from coastal erosion and climate change. Offshore infrastructure projects offer the opportunity for multidisciplinary research into submerged landscapes. The opportunities for new discoveries on the seabed have increased significantly through large scale seabed remote sensing data undertaken for the offshore renewables industry and national mapping. Application of machine learning and artificial intelligence to these massive survey datasets can assess seabed survey data to identify potential wreck sites and other obstructions. In the United Kingdom some of the challenges presented in working with the historic marine environment are being addressed in the Towards a National Collection funded ‘Unpath’d Waters’: Marine and Maritime Collections in the UK (https://unpathdwaters.org.uk/). By developing data standards, including key controlled vocabularies, and cataloguing practices Unpath’d Waters aims to improve interoperability across national heritage agency resources and unlock opportunities to work more closely with museums and archives. This session will explore:
• Solutions to harmonising marine data from across the heritage sector with the broader marine data landscape, in ways that enhance their Findability, Accessibility. Interoperability and Reusability.
• Visualisations and simulations that promote our understanding of submerged landscapes and wrecks.
• Applications of artificial intelligence and machine learning to explore marine heritage data and paleaolandscapes.
Whilst not an unknown frontier, our marine past is an underexplored frontier providing significant opportunities to apply a range of computer applications to improve the quality of the archaeological record. This session will explore how computer applications can be applied to the broad range of marine datasets to improve our knowledge and understanding of our maritime heritage and to communicate a difficult to access environment more broadly through novel techniques.
S14. Robotics and Archaeology – on the state of the art and beyond
Daniel Carvalho, UNIARQ; FCT; LAQU
Session type: Standard
Robots are an integral part of contemporary society. From healthcare to manufacture, agriculture and industrial contexts, robots play fundamental roles, indispensable to maintaining and sustaining numerous systems. Archaeology, as well as various areas, utilizes robots in its endeavors: on the field, in laboratories, in presentations to the public. From automatic typologies to UAVs that reach the depths that humans can not fathom to venture, robots aid archaeologists in concluding their tasks, in an efficient and reliable way. Is it possible to go even further and elevate the role of robots within Archaeology? Are robots to be used as extensions and tools or can we conjoin them with Artificial Intelligence, and build an Artificial Archaeologist? In this session, we intend to discuss the present state of robotics in Archaeology and dwell on the possibilities that lie in the near future. Proposals, although not exclusive, would be very welcome on these lines of thought, both concerning eventual case studies and theoretical reflections: How do archaeologists use robots, in which circumstances and what are their benefits and drawbacks; Robots and the act of the excavation – should robots do fieldwork for us? How archaeologists can use robots for building knowledge and how would it affect the discipline; What should be the ethical concerns that surround the use of robots in Archaeology?
We encourage papers from students and ECR in different phases of their research, to provide a space for showing their ongoing work and progress.
S15. Reproducing, Reusing, and Revising Code and Data in Archaeology
James R. Allison, Brigham Young University
Sophie C. Schmidt Berlin Graduate School of Ancient Studies, Freie Universität Berlin
Florian Thiery M.Sc., Römisch-Germanisches Zentralmuseum, Department of Scientific Computing and Research Software Engineering, Mainz, Germany
This session aims at evaluating how reproducible research in archaeology is actually faring. It has been argued that reproducible research techniques such as publishing and sharing code as well as data speed up scientific progress (Marwick 2017, Schmidt & Marwick 2020). With the FAIR movement and the rise of (Linked) Open Data approaches there seem to be more and more archaeological data sets available. Code used for archaeological analysis is also increasingly published online. There are a growing number of openly available code examples that have been used for articles (see for R https://github.com/benmarwick/ctv-archaeology, or for Netlogo https://www.comses.net/codebases/?query=archaeology ). In some cases, this shared code may be adapted into “little helpers”, small modules of research software, aka Little Minions (Thiery et al. 2021), that can be reused and individually adapted. The community of Research Software Engineers (RSE), people who create software applications for research, is growing. For better dissemination of these programs, they created the FAIR4RS principles (Hong et al. 2022). RSEs are fighting for scientific recognition by e.g. implementing the CFF format to cite software (Anzt et al. 2020). But despite this general progress, published articles reusing or adapting open data or code are rare in archaeology. It is difficult to assess how often code and data are reused for research, but the rate of reuse appears to be low (Huggett 2018, Marwick and Birch 2018). Open data and code may be reused more often for teaching (Cook et al. 2018, Gartski 2022, Marwick et al. 2019), but it is not clear how often this happens. In this session we would like to ask the following questions
• How often does it happen that archaeologists try to reproduce each others’ analysis, or borrow code from each other?
• Can fruitful examples be shown?
• Are there examples of replication or reproduction of analyses failing?
• Which techniques are needed to successfully reuse data and code from other persons – on the side of the provider as well as the reuser (forking, data papers, …) ?
• Are these methods taught to students and how are they taught?
• What reproducibility techniques should be focused on in the future?
• What problems arise in trying to re-use data (not just tabular, but also eg 3D and geophysical data)
By discussing these topics we want to encourage the re-use of openly available data sets and published code in archaeology. We particularly welcome papers that reuse or adapt openly available code to analyze new datasets, or papers that reanalyze existing open data in new ways. We would very much like to see contributions that generate open code to replicate previous analyses or create newly open data sets from existing data that is currently difficult to access (e.g., data found only in printed tables in reports or articles). Papers that examine the use of open data and code in teaching are also very welcome. We hope to fuel a debate about the usefulness and worthwhileness of creating open data and code. Reproducibility needs to be evaluated not just from a theoretical viewpoint but also in practice.
Anzt H., Bach F., Druskat S. et al. (2021). An Environment for Sustainable Research Software in Germany and Beyond: Current State, Open Challenges, and Call for Action [version 2; peer review: 2 approved]. F1000Research, 9:295 (https://doi.org/10.12688/f1000research.23224.2)
Chue Hong, N. P., Katz, D. S., Barker, M., Lamprecht, A-L, Martinez, C., Psomopoulos, F. E., Harrow, J., Castro, L. J., Gruenpeter, M., Martinez, P. A., Honeyman, T., et al. (2022). FAIR Principles for Research Software version 1.0. (FAIR4RS Principles v1.0). Research Data Alliance. DOI: https://doi.org/10.15497/RDA00068
Cook, K., Çakirlar, C., Goddard, T., DeMuth, R. C., and Wells, J. (2018). Teaching Open Science: Published Data and Digital Literacy in Archaeology Classrooms. Advances in Archaeological Practice, 6(2), 144–156. DOI: https://doi.org/10.1017/aap.2018.5
Garstki, K. (2022). Teaching for Data Reuse and Working toward Digital Literacy in Archaeology. Advances in Archaeological Practice, 10(2), 177-186. DOI: https://doi.org/10.1017/aap.2022.3
Huggett, J. (2018). Reuse Remix Recycle: Repurposing Archaeological Digital Data. Advances in Archaeological Practice, 6(2), 93-104. DOI: https://doi.org/10.1017/aap.2018.1
Marwick, B. (2017). Computational reproducibility in archaeological research: Basic principles and a case study of their implementation. Journal of Archaeological Method and Theory 24(2), 424-450. http://doi.org/10.1007/s10816-015-9272-9
Marwick, B., & Birch, S. (2018). A Standard for the Scholarly Citation of Archaeological Data as an Incentive to Data Sharing. Advances in Archaeological Practice 1-19, https://doi.org/10.1017/aap.2018.3
Marwick, B., Wang, L.-Y., Robinson, R., & Loiselle, H. (2019). How to Use Replication Assignments for Teaching Integrity in Empirical Archaeology. Advances in Archaeological Practice, 1–9. https://doi.org/10.1017/aap.2019.38
Schmidt, S. C., & Marwick, B. (2020). Tool-Driven Revolutions in Archaeological Science. Journal of Computer Applications in Archaeology, 3(1), 18–32. DOI: http://doi.org/10.5334/jcaa.29
F. Thiery, Visser, R. & Mennenga, M. (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: https://doi.org/10.5281/zenodo.4575168
S16. Archiving information on archaeological practices and knowledge work in the digital environment: workflows, paradata and beyond
Isto Huvila, Uppsala University
Jessica Kaiser, Uppsala University
Session type: Standard
Knowledge of archaeological work – from fieldwork and post-excavation and laboratory analyses to visualisation and beyond – is crucial for understanding and using its different outputs independently if they are digital or non-digital data, reports, or monographs, digital visualisations, or models. There is a growing corpus of empirical and theoretical research and accounts of practical work on documenting, capturing and keeping information pertaining to archaeological, scientific and scholarly practices. These studies range from the documentation of traces (e.g. Morgan & Eve, 2012), paradata (e.g. Gant & Reilly, 2017; Denard, 2012; Huvila et al. 2021) and, for example, provenance metadata (e.g. Huggett, 2014) and how information can be preserved as a part of the archaeological record. This session invites presentations of evidence-based, theoretical and reflective work relating to archiving of information that describes and documents digital archaeological practices. The session is open to quantitative and qualitative evidence-based studies of archiving and re-use of archived information on archaeological practices and knowledge work, as well as theoretical work shedding light on different, for example, epistemological aspects of the topic. Further, the session welcomes reflections and descriptions of how such information has been archived or is planned to be archived in practice. Relevant contexts for presentations discussing archiving and the implications of different types of information archived on archaeological practices and knowledge work in the digital environment range from archiving and preserving fieldwork, to the documentation of data creation (for example, database design and management), working on legacy documentation, metadata and paradata, automatic and manual archiving and beyond. Proposals are welcome from the entire CAA community including archaeologists, 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 practices. The session is affiliated with the CAASIG ARKWORK on archaeological practises and knowledge work in the digital environment.
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.
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
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
S17. Hic sunt dracones II. Applying semantic technologies, LO(U)D-based tools/workflows and Artificial Intelligence approaches to modelling real-world data-driven knowledge
David Wigg-Wolf, Römisch-Germanische Kommission des Deutschen Archäologischen Instituts
Dr. Karsten Tolle, Frankfurt Big Data Lab, Institute of Computer Science, Goethe-University, Frankfurt am Main, Germany
Brigit Danthine, M.A., Austrian Archaeological Institute (Austrian Academy of Science), Austria Mag.
Nicole High-Steskal, Ph.D., University for Continuing Education Krems Department for Arts and Cultural Studies
Florian Thiery M.Sc., Römisch-Germanisches Zentralmuseum, Department of Scientific IT, Mainz, Germany
Dr. Allard W. Mees FSA, Römisch-Germanisches Zentralmuseum, Department of Scientific IT, Mainz, Germany
Session type: Standard
In historical maps, the phrase “Hic sunt dracones” (engl. here be dragons) is used to describe areas which were unknown to the map creator. Today the WWW offers researchers the possibility of sharing their research (data) 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 re-usability . To overcome these shortcomings, Linked Open Data (LOD) techniques can be used . In 2006 Berners-Lee  introduced the concept of LOD, in 2018 Sanderson instigated the “Usable” aspect at EuropeanaTech . In addition, Artificial intelligence (AI) technologies such as machine learning (ML) and reasoning as part of the archaeological knowledge era  use and analyse this structured data to generate new knowledge. 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 and Graph Technologies / Graphs and Networks in the Humanities offer methods and resources that could be 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 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 interacting with it. AI technologies can also use structured data such as LOD, for reasoning in vagueness issues like temporal reasoning in the Academic Meta Tool [7,10] or machine learning in numismatics [8, 9]. The positive feedback on the LOD sessions on data quality, FAIR and LOUD at CAA 2017-2022 encourages the pursuit of the debate. The goal of our session is to bring together both experts and colleagues interested in learning about LOUD data-driven publishing and applications, as well as to collect research-application scenarios to jointly promote domain-specific research solutions using LOD. We would like to discuss application-oriented and data-driven investigations into how to improve technologies for 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 following issues: – applications of AI technologies based on LOD – application of semantic web technologies, such as ontologies (e.g. CIDOC-CRM) or RDF, to the archaeological domain – modelling of archaeological artefacts, and archaeological context, including the specificity of stratigraphy, uncertainty, and vagueness – development and use of research tools in archaeological research producing or using LOUD data, their implementation and/or enhancement – identifying sources of incorrect or dealing with dangers of ambiguous LOD, e. g. duplicates across different LOD sources – tracking 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 – computer vision or machine learning applications built upon controlled, semantic data – modelling reproducible workflows and data flows as “Linked Pipes”  using RDF for documentation and reproducible research – using LOD-related tools, 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 the use of LOD We encourage presenters to derive the problems addressed from real-world datasets and to formulate proposals for solutions, preferably demonstrating (prototypes of) realised data-driven (web-) applications. Due to the thematic relevance, we target a broad and diverse audience and the challenges described should also be integrated into an archaeological context (excavation, museum, archive, etc.). Only those papers will be taken into consideration which offer the data involved as FAIR data and provide the tools as Open Source in Open Science repositories (e.g. Zenodo, OSF, GitHub, GitLab). 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 data in archaeology.
 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.
 Berners-Lee, T. (2006). Linked Data. URL: https://www.w3.org/DesignIssues/LinkedData.html.
 Thiery, F., Homburg, T. (2021). Linked Pipes @ Linked Pasts 7: Introduction. Presentation at Linked Pasts VII, Ghent, Belgium. DOI: 10.5281/zenodo.5781275.
 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/.
 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.
 Thiery, F. (2019). Archaeology 4.0: Archaeology in the Third Era of Computing. Squirrel Papers, Vol. 1, Issue 1, No. 2. DOI: 10.5281/zenodo.2629595.
 Unold, M., Thiery, F., Mees, A.W. (2019). Academic Meta Tool. Ein Web-Tool zur Modellierung von Vagheit in Die Modellierung des Zweifels – Schlüsselideen und -konzepte zur graphbasierten Modellierung von Unsicherheiten. Zeitschrift für digitale Geisteswissenschaften. Volume Sonderbände 4, No. 4. DOI: 10.17175/sb004_004.
 Frankfurt-BigDataLab, Deligio, C., Tolle, K., Gampe, S. (2022). NLP-on-multilingual-coin-descriptions. GitHub Repository. Link: https://github.com/Frankfurt-BigDataLab/NLP-on-multilingual-coin-datasets
 Klinger, P., Gampe, S., Tolle, K., Peter, U. (2018). Semantic Search based on Natural Language Processing – a Numismatic example. Journal of Ancient History and Archaeology (JAHA). Volume 5, Issue 3, pp. 68-79. DOI: 10.14795/j.v5i3.334.
 Mees, A.W., Thiery, F. (2022). Linked Open Time: Reproducible LOD-driven workflows and research tools for validating Roman Limes and Hadrian’s Wall relative time intervals based on Samian (Terra Sigillata). Presentation at CAA 2022 in Oxford. DOI: 10.5281/zenodo.6976175.
 Thiery, F., Trognitz, M., Gruber E., Wigg-Wolf, D.G.. (2019). Hic sunt dracones! the modern unknown Data Dragons. Squirrel Papers, Vol. 1, Issue 1, No. 1. DOI: 10.5281/zenodo.3345715.
S18. Modelling Ancient Cities: methods, theories and tools
Katherine Crawford, The Cyprus Institute
Iza Romanowska (Aarhus Institute of Advanced Studies, Aarhus University, Denmark)
Dries Daems (Middle East Technical University, Turkey)
Session type: Standard
The city has been a major topic of interest for archaeologists from the early days of the discipline until now (Woolf 2020; Childe 1950). In recent years, scholars have increasingly come to see cities as inherently complex systems requiring a wide range of tools and specialist methods to study their functioning, evolution and transformations (Batty 2007; Shi et al. 2021; Ortman, Lobo, and Smith 2020). The application of quantitative methods for the study of ancient cities and settlement networks has likewise seen increased interest in recent years (Lobo et al. 2019; Ortman et al. 2014). Increased accessibility to large scale datasets, due to advancements in data collection, has resulted in an increasingly diverse number of studies looking at past cities from new perspectives, focusing both on their idiosyncrasies and cross-cultural comparative dimensions (Smith 2020; Baumanova and Vis 2019). At the same time, recent developments in excavation, recording and analysis techniques have enabled archaeologists to dive deep into the past of individual cities, reconstructing their built environment (Fletcher 2020), infrastructure (Crouch 1993), social-economic interactions (Smith et al. 2014) or even their inhabitant’s diets (Rowan 2017). These advancements in methods, data and theory have opened new possibilities for the study of cities and settlement systems at different scales.
This session invites papers that deal with the applications of computational and digital methods, grounded in population-level systemic thinking, but also coming from the individual perspective, that investigate the structural properties and mechanisms driving complex socio-natural urban systems. The goal is to showcase the potential of using systematically collected data on urban systems and formal analytical methods to broaden our understanding of the general mechanisms driving urban dynamics. These may include but are not limited to: agent-based modelling, network analysis, urban scaling, gravity and spatial interaction models, space syntax, GIS, and data mining applied to such topics as settlement persistence, urban social complexity, multi-scale spatial patterns within urban complexes and across settlements, inter and intra- settlement dynamics, urban-environmental processes, and city historical trajectories including urban formation and abandonment.
We look for a diverse range of studies on the interactions between cities, simulations of social and socio-natural activities, as well as analyses of groups of cities and their environment. We are especially interested in papers that adopt a large-scale comparative and diachronic perspective to studying transformations and transitions of urban and settlement systems.
Batty, Michael. 2007. Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals, Michael Batty. (version 1st MIT press paperback ed.). 1st MIT press paperback ed. Cambridge: MIT press.
Baumanova, Monika, and Benjamin N. Vis. 2019. “Comparative Urbanism in Archaeology.” In Encyclopedia of Global Archaeology, 1–11. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-51726-1_3478-1.
Childe, V. Gordon. 1950. “The Urban Revolution.” The Town Planning Review 21 (1): 3–17.
Crouch, Dora P. 1993. Water Management in Ancient Greek Cities. Oxford University Press.
Fletcher, Roland. 2020. “Urban Labels and Settlement Trajectories.” Journal of Urban Archaeology 1 (January): 31–48. https://doi.org/10.1484/J.JUA.5.120908.
Lobo, Jose, Luis MA Bettencourt, Michael E Smith, and Scott Ortman. 2019. “Settlement Scaling Theory: Bridging the Study of Ancient and Contemporary Urban Systems.” Urban Studies, October, 0042098019873796. https://doi.org/10.1177/0042098019873796.
Ortman, Scott G., Andrew H. F. Cabaniss, Jennie O. Sturm, and Luís M. A. Bettencourt. 2014. “The Pre-History of Urban Scaling.” PLOS ONE 9 (2): e87902. https://doi.org/10.1371/journal.pone.0087902.
Ortman, Scott G., José Lobo, and Michael E. Smith. 2020. “Cities: Complexity, Theory and History.” PLOS ONE 15 (12): e0243621. https://doi.org/10.1371/journal.pone.0243621.
Rowan, Erica. 2017. “Bioarchaeological Preservation and Non-Elite Diet in the Bay of Naples: An Analysis of the Food Remains from the Cardo V Sewer at the Roman Site of Herculaneum.” Environmental Archaeology 22 (3): 318–36. https://doi.org/10.1080/14614103.2016.1235077.
Shi, Wenzhong, Michael F. Goodchild, Michael Batty, Mei-Po Kwan, and Anshu Zhang, eds. 2021. Urban Informatics. The Urban Book Series. Singapore: Springer Singapore. https://doi.org/10.1007/978-981-15-8983-6.
Smith, Michael E. 2020. “The Comparative Analysis of Early Cities and Urban Deposits.” Journal of Urban Archaeology 2 (January): 197–205. https://doi.org/10.1484/J.JUA.5.121537.
Smith, Michael E., Timothy Dennehy, April Kamp-Whittaker, Emily Colon, and Rebecca Harkness. 2014. “Quantitative Measures of Wealth Inequality in Ancient Central Mexican Communities.” Advances in Archaeological Practice 2 (4): 311–23. https://doi.org/10.7183/2326-3768.2.4.XX.
Woolf, Director Greg. 2020. The Life and Death of Ancient Cities: A Natural History. New York.
S19. Building a Collaborative & Interoperable Information Ecosystem: A conversation to bridge archaeological data systems and infrastructures
Annabel Lee, Enriquez Getty Conservation Institute
Alison Dalgity, Getty Conservation Institute
David Myers, Getty Conservation Institute
Session type: Round table
The session will explore ways to foster a richer and more collaborative information ecosystem in archaeology. This landscape encompasses commercial information services and software applications, academic and nonprofit information services, and multiple open-source projects. Some of these information systems are general purpose, and some are specifically designed to meet unique information management needs in archaeology and cultural heritage.
For example, the Arches project develops open-source software to support cultural heritage data management needs and has built a strong community of organizations and people who actively use the application worldwide to document and conserve cultural heritage, including numerous implementations dealing with archaeological recording, risk assessment, and research. The project’s goal is to ensure improved data management to support effective heritage conservation and management, and ultimately to improve understanding and stewardship of cultural heritage resources by providing researchers with tools for creating, sharing, and exploring data.
But Arches is only one of a constellation of software systems and services used in archaeology. Cultural heritage professionals have many and diverse information needs that extend beyond areas that Arches currently supports. KoboToolBox, FAIMS, and others provide field data collection tools, while Pelagios offers a number of software applications and online services that help researchers use and create Linked Open Data. Besides these tools, other online data systems, including various gazetteers and collections databases, as well as digital repositories play critical roles.
The success and vibrancy of archaeological information systems depends upon a collaborative community that builds upon each other’s contributions. We are hosting a round table session including key panelists and an open discussion to explore how this diversity of applications and services can better work in concert. Questions to be explored include:
· Where might there be areas of complementarity that can be further developed?
· Can we promote workable more modular design practices so we can develop and share useful components across different projects? Would this help address “not invented here” disincentives to build upon each other’s efforts?
· What roadblocks may exist in establishing greater interoperability?
· What opportunities can be explored for collaborative partnerships?
· What lessons can we learn from one another? And, how can we collaborate and leverage the strengths and roles of each system to better serve archeological management and research, and cultural heritage in general?
S20. Simulations for the past, simulations for the future
Isaac Ullah, San Diego State University
Iza Romanowska, Aarhus University
Doug Rocks-MacQueen, Landward Research
Session type: Standard
Simulation is the closest tool we have to a time machine. It enables us to investigate past complex social and socio-natural dynamics in a robust scientific manner that overcomes some of the limitations of the archaeological record. This year marks the tenth anniversary of the regular “ABM session” at the CAA conference. In the last decade, over 50 researchers from all continents presented their models ranging in spatio-temporal scope from the earliest hominins’ global dispersal to reconstructions of particular building projects in historical times. We have tested hypotheses regarding the origins of cognition, language and art, assessed subsistence strategies of groups across virtually every Earth’s biome, looked for mechanisms driving complex human interactions such as exchange, demographics, or warfare and tried to determine what processes shaped human mobility and settlement distributions over various types of landscape or preference for particular products. However, simulation studies also opened up archaeology to bigger and more general research questions that transect the particularities of any one case study. While most models focus on a low-level research question –what has happened in a particular place at a particular time – they also give us insight into general tropes of human behaviour, interactions and response to change. These topics have been of much interest in archaeology since the earliest days, but they are more often simply discussed rather than operationalised, developed, and tested within formal, scientific frameworks. The objective of this session is therefore twofold. First, to showcase the breadth and contribution of archaeological simulation to our understanding of the past and past people. Second, to reflect on the contributions that our models make or could make in the future to addressing the grand societal challenges currently faced by humanity. We invite papers that describe research involving formal simulation modelling methods, such as system dynamics, agent-based modelling, cellular automata, etc., on any topic without restrictions regarding the scope, subject, spatial or temporal aspect, or level of completeness of the model. We ask the authors to dedicate one slide of the presentation to the question of whether and how their model could contribute to one of the UN-defined Global Goals (https://www.globalgoals.org/).
S21. 50 Years of Archaeological Simulation
Iza Romanowska, Aarhus Institute of Advanced Studies
Session type: Round table
Archaeological simulation has long roots in archaeology, comparable to other disciplines, however, its later historical trajectory differs significantly. From the optimistic beginnings, through the “dark ages” of the 1980s and the new dawn triggered by the rise of complexity science and simple modelling frameworks such as NetLogo in the 1990s and early 2000s – simulating the past had a rich but choppy history. As its popularity changed, so did the archaeologists’ perception of its role in archaeological discourse as well as topics and types of research questions tackled through modelling. Similarly, the scope and type of simulations developed by archaeologists changed over time, from the early “whole-world” equation-based system models of the 1960s to the sleek and elegant simple abstract ABMs of the early 2000s and much more complex ones in the last decade. Being a small community individual archaeological modellers played a large role in the shaping of the discipline and their particular interests, specialisms and characters had a much stronger impact than would be expected in a larger research field. The 50 anniversary of the CAA is a fantastic opportunity to critically reflect on the development of archaeological simulation. Thus, the aim of this roundtable is to look back at the history of archaeological simulation, the scholars, topics, tools and models developed in the last 50 years. Taking stock of where we stand now, we will discuss the key challenges, growth areas and actions needed to sustain the steady growth of archaeological simulation. This will hopefully allow us to sketch out the possible futures of archaeological simulation modelling. A draft overview paper will be circulated a month before the roundtable and then discussed by the panellists and the audience. The paper will be then opened to all participants so that it can be written and edited in a truly collaborative fashion. The goal is to represent the multivocality of archaeological simulation modellers across generations, theoretical traditions, different simulation methods (EBM, ABM, CA), or modelled topics. With all contributors listed as authors, we will submit the paper to the special issue of the Journal of Computer Applications in Archaeology to be considered as part of the special issue celebrating the 50 years of the CAA.
S22. Machine and deep learning methods in archaeological research – creating an integrated community of practitioners
Alex Brandsen, Leiden University
Wouter Verschoof-van der Vaart, Leiden University
Daniella Vos, University of Groningen
Session type: Standard
We are witnessing an increase of papers, sessions and discussion on Machine Learning (ML) and Deep Learning, both within CAA and outside of the conference, and it is apparent that there is plenty of interest in the application of these methods in archaeology . This interest might be partly ascribed to advances made in Deep Learning – in particular Convolution Neural Networks – across various disciplines. Applications using these methods now show high performance and in some cases exceed humans on challenging tasks ranging from computer vision to natural language processing. In digital archaeology we have seen and foresee applications of these techniques including automated object detection in remote sensing data, artefact image classification, use-wear analysis, text mining, paleography, predictive modelling, 3D shape analysis and recognition, and typology development.
The diversity of AI-based procedures, methods and archaeological applications results in a certain lack of standardised approaches, comparable accuracy metrics, and reusable workflows, leading to a “reproducibility crisis” . If we want to learn from each other, avoid common pitfalls, and together push this topic forwards within archaeology, we need to move beyond isolated case studies, and look into how we can best combine our efforts.
This session aims to: 1) offer a space for comparing methods, algorithms, code, APIs and workflows; 2) discuss the problems related to their application and; 3) offer insights into best practices including sources of error and validation methods. The ultimate aim is that the combination of approaches and the ensuing discussion will help to further build an integrated community of practitioners.
We specifically invite authors to submit papers relating to the creation of (annotated) datasets & the sharing of developed methods, data (or data structures) and code, but also welcome papers on the more broad subject of Machine Learning, relating to the following themes:
- Using small, incomplete and noisy datasets for ML;
- Choosing and tuning specific ML techniques;
- Evaluation of ML and conventions for performance metrics;
- Interpretation and validation of ML results;
- Collaboration and insights from ML fields outside of archaeology;
- Ethics of ML in archaeology;
- Education of ML in archaeology;
- Case studies on the application of ML to the analysis of texts, artistic representations, bioarchaeological remains, material culture, archaeological sites, etc. Combinations of such approaches will be particularly welcome.
For practical approaches we would encourage a critical dialogue to identify individual and shared problems, opportunities, and solutions. We invite authors to provide a thorough explanation and evaluation on their methods.
 Mantovan, L., & Nanni, L. (2020). The Computerization of Archaeology: Survey on Artificial Intelligence Techniques. SN Computer Science, 1, 267. https://doi.org/10.1007/s42979-020-00286-w
 Kapoor, S., & Narayanan, A. (2022). Leakage and the Reproducibility Crisis in ML-based Science. arXiv preprint. https://doi.org/10.48550/arxiv.2207.07048
S23. Understanding Archaeological Site Topography: 3D Archaeology of Archaeology
Gert Jan Van Wijngaarden, University Of Amsterdam
Session type: Round table
The current ubiquitous use of 3D recording technologies in archaeological fieldwork, for a large part due to the application of budget-friendly (drone) photogrammetry, has exponentially increased the availability of 3D data of archaeological sites and landscapes. Various applications, such as 3D excavation documentation, prospection, heritage management and of course visualisation/presentation have already advanced beyond the experimental phase. In this round table, we would like to discuss the application of 3D recording for the ‘Archaeology of Archaeology’ approach, which has been developed at the University of Amsterdam, see: https://www.uva.nl/en/discipline/archaeology/research/troy/troy.html. In this approach, past archaeological activities at a site are studied by archaeological means in order to elucidate how past research questions, designs, results and interpretations have influenced knowledge about a site (cf. Murray & Spriggs 2017). Within this concept, the archaeological site is regarded as a laboratory in which, often for long periods of time, scientific research has taken place that has left its traces on the site. The current geography of a site such as ancient Troy, at which the approach is currently further developed, is determined at least as much by archaeological activities as by ancient habitation (Lucas 2012). Within the Archaeology of Archaeology approach, 3D recording techniques play a key role. They allow for creating a high-resolution and accurate digital twin of the archaeological site in its current state (1), facilitating the understanding of the topography of past excavations at complex sites (i.e. the spatial definition of trenches, dumps, pathways and stratigraphy), thereby contextualizing the old records, plans and photos of past interventions. With the help of such records it will become possible to reconstruct the archaeological site in its past state, before and during successive stages of excavations (2). Perhaps most importantly, a model of the site may serve as a central 4D hub, functioning as a study resource and allowing the interaction of different types of data and archival records (3). Since 2018, these three aims are being pursued at the site of ancient Troy in Turkey, where the Archaeology of Archaeology approach is being developed. However, the conceptualization of the 3D component is still in its early stages. In this round table, we would like to have an open discussion about the potential to combine 3D recording and 3D information systems with geographical and archival information of archaeological activities at a site. Where we have Troy as a case study, we hope to discuss wider implications with the participants of this round table. We invite scholars and students who work with varied datasets at complex archaeological sites and landscapes to share their experiences and ideas.
Lucas, G. 2012, Understanding the Archaeological Record, Cambridge: Cambridge University Press. Murray, T. & M. Spriggs 2017, The Historiography of Archaeology: Exploring Theory, Contingency and Rationality, World Archaeology 49.2, 151-157
S24. How Are Archaeological Narratives about the Past Constructed? – Analysing Argumentation in Archaeology
Cesar Gonzalez-Perez, Incipit CSIC
Martin Pereira-Fariña, University of Santiago de Compostela
Raquel Liceras-Garrido, Complutense University of Madrid
Patricia Martin-Rodilla, University of A Coruña Beatriz Calderón-Cerrato, Incipit CSIC
Session type: Standard
How can data identified as a record of the cultural past be presented as evidence? How can these data support claims about the past that cannot always be verified? The elaboration of good and strong arguments is one of the key points to addressing this type of question. However, scientific publications often focus on showing how data has been obtained and analysed rather than arguing convincingly on a relatively small number of claims or points to be communicated. Especially, in the field of archaeological knowledge, arguing is particularly challenging due to its unique nature: claims about the past that cannot be indubitably verified (Lucas, 2019). Is it possible to analyse several lines of argumentation from the archaeological data to the conclusions and assess how well founded these conclusions are? The main aim of this session is to generate some cross-fertilization between argumentation theory and archaeological reason. Instead of treating the elaboration of arguments as a secondary step in the creation of archaeological knowledge, we should start considering it as an essential step, and enhance it with all the theoretical support that other studies in argumentation can provide.
The most recent work studying argumentation of archaeological knowledge (Chapman and Wylie, 2016; Lucas, 2019; Smith, 2015) has developed proposals specifically focused on how good arguments can be elaborated. They are inspired by Toulmin’s (Toulmin, 2008) model of argumentation, having several limitations related to the variety and richness of the different ways in which people build different types of arguments in the field. We argue in favour of applying state-of-the-art contributions in argumentation theory to archaeological knowledge. For instance, annotated text corpora (Fort, 2016) and Argument Analytics (Lawrence et al., 2016) can be applied as an alternative to the Toulmin model. These techniques can be used to improve the outputs generated by research work, such as reports, fieldwork diaries, or scientific publications. On the other hand, we acknowledge that different texts can provide alternative views of the same underlying data, thus developing alternative lines of reasoning. Texts sharing similar views or defending the same claims can be put together into a corpus to be annotated and studies which allows us to explore inter-textual relationships (Visser et al., 2018; Gonzalez-Perez, 2020), that is, discover how texts and authors are interconnected and how the content of various texts cross-references and relies on the meaning of others. Lastly, the computational treatment of archaeological arguments is a field to be explored. The current explosion in the development of Argument Mining (Lawrence and Reed, 2020), together with the automated reconstruction of the argumentative structure of texts, opens up the possibility of massive treatment of argumentative texts in archaeology.
Research is necessary to generate cross-fertilisation between argumentation theory and archaeological knowledge. We need to provide a good conceptualisation of the argumentation concepts (premises, conclusions, argument schemes, supports, attacks, etc.) tuned to the specific characteristics of archaeological knowledge. Only when a solid theoretical basis has been established, we will be able to refine existing computational models of argumentation to deal with archaeological texts as appropriate. Expected Themes Papers are welcome in this session about the following topics, among others:
- Philosophical accounts of argumentation
- Relationships between discourse makers and argumentation in archaeology
- Methodologies of discourse analysis applied to argumentation in archaeology
- Theories, ontologies and conceptual models of arguments in archaeology
- Uses of argument mining techniques for specific tasks in archaeological reasoning
- Annotation of archaeological texts
- Argument schemes for archaeological reasoning
- Argument analytics for archaeological arguments
- Argument analysis to question major archaeological paradigms (hunter-gatherers, gender stereotypes, state nations, complex societies, etc.)
- Visualisation of argument analytics for archaeological reasoning Audience
The session will be of interest to:
- Archaeologists concerned with a richer and more nuanced representation of archaeological reasoning
- Students working on how to better defend a claim
- Cultural heritage managers that use archaeological information for decision making • Developers of information systems aiming to capture and represent argumentation structures
- Publishers or archaeological texts interested in improving the soundness and cogency of their materials
Chapman R and Wylie A (2016) Evidential Reasoning in Archaeology. London: Bloomsbury Publishing Plc. Fort K (2016) Collaborative Annotation for Reliable Natural Language Processing: Technical and Sociological Aspects. Hoboken, NJ: ISTE Ltd/John Wiley and Sons Inc.
Gonzalez-Perez C (2020) Connecting Discourse and Domain Models in Discourse Analysis through Ontological Proxies. Electronics 9(11), MDPI.
Lawrence J and Reed C (2020) Argument Mining: A Survey. Computational Linguistics 45(4): 765-818.
Lawrence J, Duthie R, Budzynska K and Reed C (2016) Argument Analytics.
Lucas G (2019) Writing the Past. Milton: Routledge.
Smith M (2015) How can Archaeologists Make Better Arguments? The SAA Archaeological Record 15(4): 18-23.
Toulmin SE (2008) The Uses of Argument. Cambridge [u.a.]: Cambridge University Press.
Visser J, Duthie R, Lawrence J and Reed C (2018) Intertextual Correspondence for Integrating Corpora. In: Calzolari N et al. (eds) Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). Miyazaki, Japan: European Language Resources Association (ELRA), 3511-3517.
S25. CAA@50: standards of practice in computational archaeology
Philip Verhagen, Vrije Universiteit Amsterdam
Session type: Round table
Archaeology has evolved into a discipline where digital technology is pervading all aspects of the profession, whether dealing with documenting the archaeological record, analyzing data or presenting our findings within the archaeological scientific community, in education and to wider audiences. With the 50-year anniversary, we want to explore the role that CAA as a membership organization can play in shaping and maintaining shared standards of research and professional conduct in computational archaeology. In this roundtable, we want to shift the focus from the development of technological standards – which has been part of numerous CAA sessions in the past – to standards of practice. What are the core elements of ethically responsible and inclusive use of digital technology in the discipline? What is currently missing in this respect? What tensions can we identify in trying to achieve these goals, and how can we tackle them? What allies can we find within the discipline and beyond? In this roundtable, participants can give a short pitch on one of the following topics to be followed by a moderated, open discussion.
- Engaging with Open Science
- Achieving sustainability of practice
- Embedding inclusive approaches
- Ethical guidelines
The outcomes of the debate will be used to explore the possibility of setting up a Special Interest Group.
S26. For a Bright Future: Challenges and Solutions for the Long-Term Preservation of 3D and Other Complex Data in Digital Cultural Heritage
George Alexis, Pantos University of Oslo, Museum of Cultural History, Department of Collection Management
Session type: Standard
The age of digital documentation has dawned. Fully digital methods (e.g., the use of total stations, photogrammetry, laser scans, computer modelling, etc.) are used in fieldwork as well as in analysis and communication on a regular basis. Once an exception, these complex and multidimensional data tools are increasingly the rule, and their output often exceeds both the technological capacity and the workflows of existing institutional infrastructure. Specialist repositories such as the Archaeological Data Service (ADS), the Digital Archaeology Record (tDAR) and others have pioneered approaches to long-term data storage, based around international standards and concepts such as the Open Archival Information System OAIS (CCSDS 2012). However, the volume and variety of primary data have transformed the data storage landscape. As highlighted by Moore et al. (2022), there remains a high degree of variability in archiving approaches, not only across different specialisms but also within individual communities. At the same time, innovation and the wider adoption of technology in society are set to continue. It remains to be seen whether the broader application of the London Charter (Denard 2012), the FAIR principles (Wilkinson 2016) or new standards from the widely anticipated Metaverse (Metaverse Standards Forum) will be a positive standardising force or whether the developing technologies will only exacerbate existing challenges. The OAIS archiving strategy requires the stakeholders of a shared domain to enter into dialogue with one another for the purpose of developing a meaningful preservation plan. After all, the plan will require not only the expertise and perspective of the data managers, but also of those producing and supplying the data and the downstream data consumers. This session sounds the call for further discussion. It invites papers that present strategic and theoretical approaches to the preservation and future reuse of complex digital data, as well as examples of practical workflows which achieve this aim. We are looking for participation from governmental institutions and private companies as well as individual researchers, and for papers that encourage debate. We ask that submissions include a brief introduction to the organisation represented and recommend that the papers be based on a 3D-data case study, although discussions of other types of complex digital data are also welcome. The aim of the session is to spread awareness of different approaches and outlooks, to spark an international dialogue with broad participation, and contribute to building the foundations for a bright future in digital cultural heritage.
ADS Archaeology Data Service, https://archaeologydataservice.ac.uk, date accessed: 19 Aug 2022. ▪ CCSDS (2012) Reference model for an open archival information system (OAIS). https://public.ccsds.org/pubs/650x0m2.pdf, date accessed 19 Aug 2022.
Denard H. (2012) A New Introduction to the London Charter. In: Bentkowska-Kafel A., Baker D., Denard H. (eds.) Paradata and Transparency in Virtual Heritage Digital Research in the Arts and Humanities Series, 57-71. https://www.londoncharter/introduction.html, date accessed 19 Aug 2022.
Metaverse Standards Forum, http://metaverse-standards.org, date accessed 19 Aug 2022.
Moore J., Rountrey A., Scates Kettler H. (2022) 3D Data Creation to Curation: Community Standards for 3D Data Preservation, https://www.ala.org/acrl/sites/ala.org.acrl/files/content/publications/booksanddigitalresources/digital/9780838939147_3D_OA.pdf, date accessed 19 Aug 2022.
tDAR Digital Archaeological Record, https://www.tdar.org, date accessed: 19 Aug 2022.
Wilkinson M. D. et al. (2016) The FAIR Guiding Principles for scientific data management and stewardship. Scientific data, 3(1), 1–9. https://doi.org/10.1038/sdata.2016.18.
S27. Exploring new ways of visualizing archaeological data
Ralf Vandam, Vrije Universiteit Brussel
Georgia Panagiotidou, UCL Interaction Centre
Session type: Standard
Data visualisations are becoming common research tools in humanistic inquiry. Besides outputs of modelling efforts and communication tools, data visualisations help bring new perspective to otherwise familiar data (Lev Manovich, 2015). However, while visualisations for encouraging such rich and varied exploration are being developed in neighbouring fields of literature and cultural studies, archaeology seems to have few such explorative examples outside the use of GIS (Gupta and Devillers, 2017). Explorative interfaces created for humanistic research are made generous in their browsing (Whitelaw, 2015), speculative and playful in their interaction features (Hinrichs, Forlini, & Moynihan, 2016), semantically rich in their layouts (Gortana, von Tenspolde, Guhlmann, & Dörk, 2018) and critical in their points-of-view (Drucker, 2015). GIS allows for more efficient management and analysis of the collected spatial data and provides an easy way to map spatial archaeological data. However, traditional GIS mapping does not easily support temporal data, which can lead to a reduction of the complexity of archaeological phenomena (Andrienko et al. 2010). In this session we want to explore new ways of visualizations to better handle the different dimensions of (spatial) archaeological datasets to reveal new patterns and create new knowledge. Among others we are hoping to explore questions such as: How to visually unpack multidimensional datasets from long-running archaeological projects? What novel visualization techniques can highlight so far undervalued perspectives of spatial data? How can the inevitable uncertainties underlying the data be communicated in visualizations? While we welcome all types of visualization, the session hopes to attract papers with customized geovisualizations and non-traditional GIS mapping of archaeological data. The session aims to provide a stimulating discussion to identify problems and opportunities. We invite authors to provide a good insight into their methods.
Andrienko, G., N. Andrienko, U. Demsar, D. Dransch, J. Dykes, S.I. abrikant, M. Jern , M.J. Kraak , H. Schumann and C. Tominsk (2010). Space, time and visual analytics. International Journal of Geographical Information Science, 24(10), 1577–1600.
Drucker, J. (2015). Graphical Approaches to the Digital Humanities. In A New Companion to Digital Humanities. https://doi.org/10.1002/9781118680605.ch17 Gortana, F., von Tenspolde, F., Guhlmann, D., &
Dörk, M. (2018). Off the Grid: Visualizing a Numismatic Collection as Dynamic Piles and Streams. Open Library of Humanities, 4(2), 1–25. https://doi.org/10.16995/olh.280
Gupta, N. and R. Devillers (2017) Geographic visualization in archaeology, Journal of Archaeological Method and Theory, 24 (3):852-885.
Hinrichs, U., Forlini, S., & Moynihan, B. (2016). Speculative Practices: Utilizing InfoVis to Explore Untapped Literary Collections. IEEE Transactions on Visualization and Computer Graphics, 22(1), 429–438. https://doi.org/10.1109/TVCG.2015.2467452
Lev Manovich. (2015). Data Science and Digital Art History. International Journal for Digital Art History, (1). https://doi.org/https://doi.org/10.11588/dah.2015.1.21631
Whitelaw, M. (2015). Generous Interfaces for Digital Cultural Collections. DHQ: Digital Humanities Quarterly, 9(1). Retrieved from http://www.digitalhumanities.org/dhq/vol/001/2/index.html
S28. Digital Humanities, Digital Archaeology
Patricia Martin-Rodilla, University of A Coruña (Spain)
Cesar Gonzalez-Perez, Incipit CSIC (Spain)
Raquel Liceras-Garrido, Complutense University of Madrid (Spain)
Maria Elena Castiello, University of Bern (Switzerland)
Christophe Tufféry, Inrap, Paris (France)
Session type: Round table
At CAA 2022 in Oxford, the roundtable “Archaeology and Digital Humanities: The Road Already Travelled and the Road Ahead” produced a fruitful discussion on the commonalities and differences between Digital Humanities and Digital Archaeology, two fields that have seemingly evolved in parallel over the last two decades without much interchange. There is a chapter on “Computing for archaeologists” in (Schreibman et al., 2004), where the authors describe a barrier to the inclusion of archaeology as part of the Digital Humanities in these terms: “The discipline at large has not fully absorbed the need to preserve access to digital data for future scholars. It has not yet found an effective and relatively standard way to present digital data as part of a final publication. Its educational institutions have not accepted the need to prepare all archaeologists in the use of those computer technologies necessary in the field and the laboratory. In part, these problems reflect the nature of the discipline, a uniquely fragmented one consisting of practitioners who may have begun as historians, art historians, students of ancient languages, or anthropologists – but not as scientists dependent upon a tradition of prompt and full data sharing. The problems also reflect the unique independence of archaeologists, who must have a strong entrepreneurial spirit in order to fund and operate complex projects.” Of course, many of these barriers have been eased since then. A subsequent edition of the same work, (Schreibman et al., 2016), however, focuses on the methodologies and technologies used by the Digital Humanities rather than the epistemological or theoretical grounds of these fields, somewhat diluting their relationship. In addition, (Huggett, 2012) also points out that the relationships between digital archaeology and the Digital Humanities are difficult to determine, given the vagueness with which Digital Humanities have been described. This issue compounds the problem of tracing and studying the relationships between the two disciplines. In any case, the fact that both fields have been coexisting for decades and generating academic, professional, and disciplinary knowledge separately but bringing together very similar works in methodologies, approaches, and technologies merits a profound reflection on the implications and consequences of seeing archaeological computing as a branch of the Digital Humanities. The recent and ongoing evolution of digital practices in archaeology is reflected in the growing importance of contributions (articles, tools, events) from professionals who are not archaeologists. For some of them, mainly in archaeometry and archaeosciences, their training profile is often that of engineers from the sciences of the earth and the universe, with specialized skills in mathematics, statistics, model designing, computer and data science, programming languages. How can archaeologists cross points of view, compare conceptual models, make coexisting different criteria for the administration of proof? The round table will generate an open debate in which three guest speakers will offer position papers for and against placing archaeological computing work within the sphere of Digital Humanities, motivating the advantages and disadvantages of doing so, and delving into the possible weaknesses and strengths of doing so, showing real examples and/or collaborations. The main objective is to continue shedding light on this disciplinary relationship. The guest speakers will be invited considering their contributions to these fields, and ensuring that a diverse and comprehensive set of viewpoints are presented. Guest speakers (and hopefully attendees) will address these topics:
- What is Digital Humanities? What is Digital Archaeology?
- What are the commonalities and differences between the two fields in terms of theory, methods, techniques, and results?
- How are multi-, inter- and trans-disciplinarity issues handled by each field?
- Which of these differences are accidental, and which essential?
- Can or should Digital Archaeology be considered part of the Digital Humanities?
- How can Digital Archaeology benefit from the advance in Digital Humanities and vice versa?
- What converging strategies are possible and adequate between the two fields?
Huggett, J. (2012). Core or Periphery? Digital Humanities from an Archaeological Perspective. Historical Social Research / Historische Sozialforschung, 37(3 (141)), 86–105. http://www.jstor.org/stable/41636599 Schreibman, S., Siemens, R., & Unsworth, J. (Eds.). (2004). A Companion to Digital Humanities. Blackwell. http://www.digitalhumanities.org/companion/ Schreibman, S., Siemens, R., & Unsworth, J. (Eds.). (2016). A New Companion to Digital Humanities (second edition). Blackwell.
S29. How do we ensure archaeological data are usable and Reusable, and for whom? Putting the R in FAIR for archaeology’s data
Sara Perry, MOLA (Museum of London Archaeology)
Holly Wright, Archaeology Data Service (ADS), University of York, UK
Session type: Standard
The last decade has seen extensive efforts to make digital assets more accessible and dynamic through experimentation with interoperability in cultural heritage aggregation infrastructures (e.g., the Europeana or ARIADNE portals). Such infrastructures allow static resources to be updated and cross-searched, but to do so, the metadata for these assets must be mapped in a centralised and controlled way. This can take the shape of mapping to a controlled vocabulary, thesaurus or ontology, which invariably reflects the types of terminology and relationships defined by those who are charged with curating the data (domain specialists), not those who might use the data in new and innovative ways. Digital data curation for cultural heritage has therefore reached a critical impasse. A central tension exists between the need to preserve cultural resources, and the dynamic potential for their use and reuse in democratic, just and compelling ways. At the same time, the introduction of the tetrarchy of FAIR Guiding Principles (Findable, Accessible, Interoperable, Reusable) for scientific data management and stewardship (Wilkinson et al. 2016) has set an important challenge: that each of the four principles is of equivalent importance and must therefore be engaged with equally. Within archaeology, much work has been done over the last 20 years to make data Findable, Accessible and Interoperable, but very little is understood about whether data are Reusable–and by whom (Wright and Richards 2018). The impact of this gap in knowledge is profound, as cultural heritage data are increasingly drawn into divisive debates, dangerous speech, cross-border misinformation-sharing and xenophobia, therein compromising human solidarity and social cohesion (e.g., Bonacchi and Krzyzanska 2021). Newly-funded through the Transformations: Social and cultural dynamics in the digital age programme of the Collaboration of Humanities and Social Sciences in Europe (CHANSE) Consortium, Transforming Data Re-use in Archaeology (TETRARCHs) argues that the future of digital curation depends upon reconciling this divide between collection and reuse. It aims to demonstrate that data optimised for ethical and emotive storytelling will provide the bridge between those who find or preserve heritage assets, and the diverse cross-European audiences for whom they might generate meaning. TETRARCHs builds upon international initiatives which seek to improve the accessibility of digital cultural heritage data via interfacing with those data: browsing them, searching them, and retrieving them in more ‘generous’ ways (e.g., (Whitelaw 2015). However, even as such experimentation grows, the assets themselves continue to be bound by relatively narrow classifications imposed by experts. Herein structure and reliability are maintained, but relevance and accessibility to the wider world remain limited (Manzo et al. 2015). The stories that can be told through the data are often narrow and pre-determined, with the vast majority devoid of affect, sensuality and agency (Krmpotich and Somerville 2016). The urgency of the predicament is heightened by growing interdisciplinary acknowledgement that this rift is directly linked to systemic bias, social inequity and racial injustice in data repositories (Sanderson and Clemens 2020). Efforts to rectify these biases include archival redescription (Pringle 2020), revised ethical metadata standards (Farnel 2018), felt-experience conceptual model extensions (Canning 2018), and alternative ‘fluid ontologies’ (Srinivasan 2018). The imperative for change to data infrastructures is overt. Yet recognition that such change must begin from the moment the data are conceived (as opposed to the moment they are deposited into a repository) has been slow in coming. Furthering our argument is the rapid pace of innovation with data acquisition technologies (Morgan et al. 2021), whose workflows still fail to capture important descriptive detail, emotion, human values and multiple viewpoints. Even as community-driven practices grow in popularity, fundamental redesign of our workflows and data to embed communities and justice at their core is still lacking (Dolcetti et al. 2021). Design Justice frameworks enabling such value-led, co-created redesign of digital structures are blossoming (Costanza-Chock 2020), but their systematic use in fields like archaeology is effectively nonexistent. Through an interdisciplinary team of archaeological specialists, data scientists, and museum practitioners, collaborating with three key user groups – domain experts, creative practitioners, and memory institutions – TETRARCHs will offer those who gather, curate and apply cultural heritage data with critically-aware workflows to prepare their data for enhanced re-use at every point in the data lifecycle (e.g., capture, mapping, lab-based analysis), then scenario-test such re-use through the dissemination of new narrative outputs authored by cross-European creative practitioners. The project embraces three scales of data collection in archaeology – landscape, site and artefact – exploring them via four increasingly ubiquitous technologies for data capture: airborne LiDAR, 3D scanning, digital field drawing and photography. Alongside novel workflows for field, post-excavation and archival practice, TETRARCHs will produce a controlled vocabulary for cultural heritage storytelling, assessments of data reuse effectiveness following ISO Standard 25022: Measurement of Quality in Use, and best practice recommendations for trusted digital repositories to optimise archaeological data for re-use. This session invites papers on the use and reuse of archaeological data, including case studies, examples of challenges and good practices, provocations and blue-sky thinking for the future of data re/use. Contributors may wish to engage with the themes of TETRARCHs or stretch beyond them. By hosting this session early in the life of TETRARCHs, we hope to foster discussion and collaboration with others who have comparable interests, and ensure that our outcomes are shaped in concert with such intersecting work, and are meaningful to the CAA community at large.
Bonacchi, Chiara, and Marta Krzyzanska. 2021. “Heritage-Based Tribalism in Big Data Ecologies: Deploying Origin Myths for Antagonistic Othering.” Big Data & Society 8 (1): 20539517211003310. Canning, Erin. 2018. “Documenting Object Experiences in the Art Museum with CIDOC CRM.” In . http://www.cidoc2018.com/sites/default/files/CIDOC2018_paper_141_0.pdf.
Costanza-Chock, Sasha. 2020. Design Justice: Community-Led Practices to Build the Worlds We Need. The MIT Press.
Dolcetti, Francesca, Claire Boardman, Rachel Opitz, and Sara Perry. 2021. “Values-Led Design Cards: Building Ethically Engaged Archaeology and Heritage Experiences.” Sustainability: Science Practice and Policy 13 (7): 3659.
Farnel, Sharon. 2018. “Metadata as Data: Exploring Ethical Metadata Sharing and Access for Indigenous Resources Through OCAP Principles.” Proceedings of the Annual Conference of CAIS / Actes Du Congrès Annuel de l’ACSI, July. https://doi.org/10.29173/cais974.
Krmpotich, Cara, and Alexander Somerville. 2016. “Affective Presence: The Metonymical Catalogue.” Museum Anthropology. https://doi.org/10.1111/muan.12123.
Manzo, Christina, Geoff Kaufman, Sukdith Punjasthitkul, and Mary Flanagan. 2015. “‘By the People, For the People’: Assessing the Value of Crowdsourced, User-Generated Metadata.” DHQ: Digital Humanities Quarterly 9 (1).
Morgan, Colleen, Helen Petrie, Holly Wright, and James Stuart Taylor. 2021. “Drawing and Knowledge Construction in Archaeology: The Aide Mémoire Project.” Journal of Field Archaeology, October, 1–15.
Pringle, E. 2020. “Provisional Semantics. AHRC: Towards a National Collection, Interim Report.” AHRC. https://www.nationalcollection.org.uk/sites/default/files/2021-01/Provisional%20Semantics.pdf.
Sanderson, R., and A. Clemens. 2020. “Libraries, Archives and Museums Are Not Neutral: Working Toward Eliminating Systemic Bias and Racism in Cultural Heritage Information Systems.” In . https://www.digitalmeetsculture.net/wp-content/uploads/2020/11/Euromed2020_BOOKLET-1.pdf.
Srinivasan, Ramesh. 2018. Whose Global Village?: Rethinking How Technology Shapes Our World. NYU Press.
Whitelaw, Mitchell. 2015. “Generous Interfaces for Digital Cultural Collections.” https://openresearch-repository.anu.edu.au/handle/1885/153515.
Wilkinson, Mark D., Michel Dumontier, I. Jsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, et al. 2016. “The FAIR Guiding Principles for Scientific Data Management and Stewardship.” Scientific Data 3 (March): 160018.
Wright, Holly, and Julian D. Richards. 2018. “Reflections on Collaborative Archaeology and Large-Scale Online Research Infrastructures.” Journal of Field Archaeology 43 (sup1): S60–67.
S30. Crossing Landscapes of the Past: Developments in Modelling Mobility and Connectivity in Archaeology
Andrew McLean, University of Edinburgh
Xavier Rubio-Campillo, Universitat de Barcelona
Session type: Standard
Recent trends show that the variety of computational approaches available for modelling mobility and connectivity across past societies are numerous and diverse. In the past employing techniques such as network analysis agent based modelling simulations or GIS to shine far greater light on the cost mobility and connectivity associated with the movement of goods and people across ancient landscapes. Advances in simulations network analysis and more complex GIS based connectivity models can be clearly noted in disciplines such as ecology but many of these new perspectives have yet to be widely adopted or discussed in archaeological contexts. Fairly well established techniques such as Least Cost Path (LCP) analysis remain the most common approaches and can provide insight into routes and journey times. However LCP is limited in the data it can provide beyond optimal routes between two fixed points. Furthermore while maritime movement was of major importance across the ancient world applying such analyses to these more complex contexts is an arduous undertaking. There have been attempts to address the difficulties with LCP but these need to be more widely discussed and understood. Innovative new methodologies have the potential to offer greater scope for improving quantitative studies. The aim of this session is to bring together scholars and researchers utilising the most cutting edge techniques for understanding movement across past landscapes. These techniques can be aimed at modelling new and more complex scenarios or presenting methods for overcoming some of the issues with the more well established techniques. It is especially hoped that researchers working with methods for understanding movement that are less widely understood in archaeology will contribute and help to improve our overall understanding of this ever evolving subject matter. We welcome speakers studying traditional LCP or network analysis for terrain beyond the purely terrestrial such as maritime or fluvial. Beyond this we are particularly eager for papers that discuss new techniques that are not necessarily well known in archaeology (or beyond) but which have a strong focus on quantitatively modelling mobility and/or connectivity across ancient landscapes. With all of this we hope to foster discussion of the most current and promising approaches to modelling mobility and connectivity available to archaeologists.
Arcenas S. (2015). ‘ORBIS and the Sea: a model for maritime transportation under the Roman Empire’ Stanford ORBIS Project
Brodie J.F. Mohd‐Azlan J. and Schnell J.K. (2016). ‘How individual links affect network stability in a large-scale heterogeneous metacommunity’ Ecology 97.7: 1658–1667. Gustas R. and Supernant K. (2017). ‘Least cost path analysis of early maritime movement on the Pacific Northwest Coast’ Journal of Archaeological Science 78: 40–56.
Hazell L.C. and Brodie G. (2012). ‘Applying GIS tools to define prehistoric megalith transport route corridors: Olmec megalith transport routes: a case study’ Journal of Archaeological Science 39.11: 3475–3479.
Herzog I. (2014). ‘Least-cost Paths – Some Methodological Issues’ IA .36:
Indruszewski G. and Barton C.M. (2008). ‘Cost surface DEM modelling of Viking Age seafaring in the Baltic Sea’ in B. Frischer and A. Dakouri-Hild (eds.) Beyond Illustration: 2D and 3D Digital Tools for Discovery in Archaeology (BAR International Series 1805). Oxford
Llobera M. Fábrega-Álvarez P. and Parcero-Oubiña C. (2011). ‘Order in movement: a GIS approach to accessibility’ Journal of Archaeological Science 38.4: 843–851.
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: McRae B. Shah V. and Edelman A. (2016). Circuitscape: modeling landscape connectivity to promote conservation and human health.
Pelletier D. Clark M. Anderson M.G. Rayfield B. and Wulder M.A. (2014). ‘Applying Circuit Theory for Corridor Expansion and Management at Regional Scales: Tiling Pinch Points and Omnidirectional Connectivity’ PLoS ONE 9.1: 1–11.
Rubio-Campillo X. Ble E. Pujol À. Sala R. and Tamba R. (2022). ‘A Spatial Connectivity Approach to Landscapes of Conflict: Julius Caesar and the Assault to Puig Ciutat (NE Iberian Peninsula)’ J Archaeol Method Theory
Yubero-Gómez M. Rubio-Campillo X. and López-Cachero J. (2016). ‘The Study of Spatiotemporal Patterns Integrating Temporal Uncertainty in Late Prehistoric Settlements in Northeastern Spain’ Archaeological and Anthropological Sciences 8.3: 477–490.”
S31. Better Together: Exploring methods and applications for the synergy of multiproxy data in the study of archaeological mobilities
Christianne Fernée, University of Bristol
Konstantinos P. Trimmis, University of Bristol
Session type: Standard
Archaeological data are inherently multi-layered, commonly fragmented, and interpretations of past events are usually based on a variety of datasets that are often not linked together or aligned. To date, the problematic nature of archaeological datasets is well documented, and sparked the early criticism of endeavours in New Archaeology (e.g. Earle and Preucel 1987; Hole 1980; Hurst Thomas 1978; Shanks and Tilley 1982). However, as suggested by Hurst Thomas, ‘trends in research swing back and forth like a pendulum’ (1978: 240), thus meticulous analysis of archaeological datasets through applications of statistical and computational modelling are again the norm. In the last decade the interpretational ‘gap’ between the descriptive and testing statistical applications has been reconciled. The introduction of Data Science and Artificial Intelligence (AI) to the archaeological discourse are helping archaeologists to gain a deeper understanding of their data (see Fernée and Trimmis 2021). The involvement of these disciplines in the field of archaeology has the potential to pave the way for the integration of different datasets, brought together to address archaeological questions. Interpretations of archaeological data are not just increasingly based upon computational methods, but also on multi-proxy approaches. In this session we are interested in multiproxy approaches that have been developed to record, interpret and understand mobilities. It is common for projects to bring together quantitative data from multiple proxies, such as isotopes, radiocarbon dating, organic residue analysis and petrography, with qualitative approaches, and occasionally creative approaches, such as creative writing, applied arts, drama, and theatre (see methods discussion in Skeates 2010 for example). In addition to these multiple proxies, archaeological theory is also advancing, suggesting ways that interpretation can be broader, inclusive, less biased and more tailored to the societies under study. In this session, mobility refers to any form of human movement. From the short—term movement of people through spaces and places, singular migration events, to fully nomadic lifeways. The footprint of mobility results in data in many forms that gives insight into different aspects of mobility. Some of these include: 1) geographical information, from archaeological isotopes and aDNA, 2) biological implications, with evidence of the impact on the human body, and 3) material culture variations, with the replacement, continuation or transitions of material culture. Thus, a question arises; How can we achieve data synergy by bringing together so many different types of data, ways of collection, analysis, and interpretation, to help us record, interpret, and understand archaeological mobilities and their impact? Data synergy is employed in this session to describe data from multiple sources and/or disciplines that, when combined, are more valuable than any of the sources alone (see Higginson et al 2018). Regardless of the type of dataset, in this session, we contend that good data is dependent on four interlinking dimensions: a). Time (synchronising the collection and sharing of data), b). People (coordinating the collection and sharing of data), c). Technology (establishing the different technologies so that data can be transmitted), and d). Quality (ensuring data is good enough for the research purpose) (see Higginson et al 2018). The discussion will examine challenges in relation to these dimensions in order to make recommendations for the development of a data synergy protocol for use in multiproxy and multidisciplinary projects. In this session, we would also like to further expand the discussion onto ways that synergy can be achieved between quantitative and qualitative approaches, and approaches that link data analysis with thick description in an archaeological context. The session aims to present and discuss methods, applications, and case studies that advance data synergy in the study of archaeological mobility. The session welcomes papers that focus on but are not limited to: a) Discussing novel computational methods that advance the synergy of data collection, curation, analysis, interpretation, visualisation, and archiving. b) Presenting case studies where these synergies have been tested or achieved. c) Discussing ethics and good practice of such synergies in archaeological contexts. d) Presenting software applications, ‘how to’ ways, and solutions that communication and synergies can be achieved. e) Discussing future challenges that synergies can face on the landscape of the ever-increasing data qualities, quantities, and types. Overall, this session would like data science to be in synergy with current archaeological theory, that views archaeological evidence of mobility (and beyond) as more connected and entangled. People, as they move through space and between places, are in a constant and everlasting interaction with their surroundings, their own and other cultures. Archaeology, however, often look at people, environments, and material culture as single strands of evidence that can assist towards a better understanding of the past; and the consequent modelling of the future. We welcome researchers that are working to bring these strands together, particularly those working at the intersection between data science and archaeology. By bringing these researchers together this session hopes to advance a better understanding of how different data can work better together for the study of human mobility.
Earle, T.K. and Preucel, R.W. 1987. Processual archaeology and the radical critique Curr. Anthropol., 28 (4) pp. 501-538 http://www.jstor.org/stable/2743487
Fernée, C. L. and Trimmis, K. P. 2021. Detecting variability: A study on the application of bayesian multilevel modelling to archaeological data. Evidence from the Neolithic Adriatic and the Bronze Age Aegean, Journal of Archaeological Science, 128, https://doi.org/10.1016/j.jas.2021.105346
Higginson, S., Topouzi, M., Andrade-Cabrera, C., O’Dwyer, C., Darby, S., Finn, D. 2018. Achieving Data Synergy: The Socio-Technical Process of Handling Data. In: Foulds, C., Robison, R. (eds) Advancing Energy Policy. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-319-99097-2_5
Hole, B. L. 1980. Sampling in archaeology: a critique. Annu. Rev. Anthropol., 9 (1980), pp. 217-234, 10.1146/annurev.an.09.100180.001245
Hurst Thomas, D. 1978. The awful truth about statistics in archaeology. Contributions to archaeological method and theory. Am. Antiq., 43 (2) , pp. 231-244, 10.2307/279247
Shanks, M. and Tilley, C. 1982. Ideology, symbolic power, and ritual communication: a reinterpretation of Neolithic mortuary practices. In I. Hodder (Ed.), Symbolic and Structural Archaeology1, Cambridge University Press, Cambridge pp. 29-154
Skeates, R. 2010. An archaeology of the senses: prehistoric Malta. Oxford: Oxford University Press.
S32. A Bridge too Far. Heritage, Historical and Criminal Network Research
Lena Tambs, University of Helsinki
Marta Lorenzon (University of Helsinki)
Arianna Traviglia (Centre for Cultural Heritage Technology-Istituto Italiano di Tecnologia)
Michela De Bernardin (Centre for Cultural Heritage Technology-Istituto Italiano di Tecnologia)
Session type: Standard
Over the last decades, ancient historians and archaeologists have slowly realised the potential network science holds for studying past phenomena and better understanding the relationships that connect entities under study. By now, we have employed diverse network perspectives to explore a variety of sources and datasets that help us shed light on the past (for overviews, see e.g. Brughmans 2013; Collar et al. 2015; Crabtree & Borck 2019; Knappett 2013; Knappett 2020; Peeples 2019; Rollinger 2020). We have built and analysed networks to answer questions about social and interpersonal networks, trade routes, production and consumption patterns, group behaviour, diffusion of ideas and technologies, social mobility, and other complex phenomena (Brughmans 2021; Cline and Cline 2015; Verhagen 2018).
Networks have been popular in diverse disciplines such as biology and physics, and their application and full implementation to archaeology emphasises the structural representation of the relationship between objects, people and places, guiding recent discovery on land use, ancient demography, past economies and trade (Brughmans 2013, 2021; Graham 2006; Verhagen et al. 2019). While not yet fully explored in the area of art-related crimes and in connection with issues of illicit trafficking in cultural heritage (Tsirogiannis and Tsirogiannis 2016), network analysis has also been successfully used to study degrees and manner of relations among criminal individuals and groups, and to investigate other forms of criminal organised trades, such as human (Vivrette 2022), drugs (Tsai et al. 2019) and wildlife trafficking (Costa 2021). It is, therefore, interesting to survey further intersections of network analytical applications to multiple fields, both in micro and macro perspectives.
Network science offers a plethora of conceptual and digital tools that allow networks to be measured and explored with formal methods, and archaeologists, historians and digital humanists have found aspects of Social Network Analysis (SNA) particularly useful (for an introduction to SNA, see e.g. Graham et al. 2016: 195-234. For handbooks, e.g. Borgatti et al. 2013; Scott 2017; Wasserman and Faust 1994). Learning to handle the uncertainty of the data and refining network modelling techniques are, however, paramount for a correct and scientific reconstruction of past interactions (Birch and Hart 2021; Carreras et al. 2019; Verhagen et al. 2019).
Even within the subfield of SNA, a range of methods and software packages are available for researchers and they provide analytical tools for exploratory as well as descriptive analysis (links below). Their relevance depends on the researchers’ topic, source material, dataset, financial means, technical skills, etc. – all of which may be decisive factors when choosing ones software (Graham et al. 2016: 237-240). For small datasets, the MS Excel extension NodeXL might suffice, but Gephi – which is freely available, works on all platforms, offers a variety of tools and plugins, is relatively easy to learn and has buttons to press (in exchange for code to be written) – quickly became popular in historical and archaeological network studies. For larger datasets or more complex statistical and network analysis, UCINET, Pajek or R might be more appropriate, but they require the researcher to engage more directly in the calculations and thus have steeper learning curves. For visualising and analysing networks that are dynamic, multivariable, longue durée or have a particularly strong emphasis on spatial data, yet other applications – like Nodegoat or the Vistorian, which are more specialised towards archaeological and/or historical data – might be the preferred choice. And often, the best solution might be to form interdisciplinary research teams (Verhagen et al. 2019: 237-238).
Since archaeologists and historians tend to work with different source materials and research questions, they are likely to utilise different software or apply different tools offered by them. The fields of historical network research and archaeological network analysis have thus developed in different directions – with historians more commonly exploring social whole or ego networks and particularly central figures in them, and archaeologists e.g. placing a larger emphasis on spatial data and compatibility with Geographical Information System (GIS), Least-Cost Path (LCP) analysis and other types of modelling (Benvan and Wilson 2013, Carreras et al. 2019; Groenhuijzen and Verhagen 2016; Lewis 2021; Verhagen 2018; Verhagen et al. 2019: 233ff.). Scholars who routinely employ network analysis to study archaeological and historical data nevertheless have a lot of common ground, in that they strive to increase our knowledge of the past through distinct network approaches and face many of the same challenges in the process (Brughmans et al. 2016; Ryan and Ahnert 2021: 61f.).
Roughly a decade ago, Lemercier (2012) and Brughmans (2013) reported general unawareness of the history, underlying sociological theories, and diversity of existing network approaches in history and archaeology respectively. That many new and creative studies have since seen the light of day is for instance reflected in the events of the flourishing Connected Past community and the online bibliography and newly launched Journal of Historical Network Research (links below). Studies critically testing the performance and robustness of formal measures on network models of the past further indicate that the fields have matured and progressed (Groenhuijzen and Verhagen 2016; Ryan and Ahnert 2021; de Valeriola 2021).
Despite an increasing number of network studies in archaeology and history, Holland-Lulewicz and Thompson (2021: 2) recently reported, that “such applications remain limited to cases employing either solely archaeological evidence or solely documentary evidence”. Acknowledging that increased dialogue between the two communities can help raise awareness of relevant (combinations of) tools and inspire new projects, methodologies and collaborations, this session aims to strengthen the ties between historically, archaeologically and cultural heritage oriented network researchers by bringing them together to discuss, share experiences and showcase relevant methods. In doing so, it welcomes papers that integrate the communities, studying both written and archaeological evidence, reflecting on the directions one or both subfields are taking, presenting research from collaborative teams, etc.
In striving to create an interdisciplinary, inclusive and diverse platform for such discussions, we encourage scholars working on all periods and geographical regions – regardless of background, identity, field and affiliation – to submit an abstract on active case studies. Research topics could include (but are not limited to):
- skills transfer in archaeology;
- modern use of archaeological data in the political discourse;
- illicit trafficking of cultural heritage;
- past and contemporary trade networks;
- interpersonal relations of individuals and groups;
- linguistic and semantic networks;
- dynamic network models;
- software and methods for studying historical and archaeological data.
Bevan, A., and Wilson, A. 2013. Models of Settlement Hierarchy Based on Partial Evidence. Journal of Archaeological Science 40: 2415–2427. https://doi.org/10.1016/j.jas.2012.12.025.
Birch, J., and Hart, J.P. 2021. Conflict, Population Movement, and Microscale Social Networks in Northern Iroquoian Archaeology. American Antiquity 86 (2): 350–367. https://doi.org/10.1017/aaq.2021.5.
Borgatti, S.P., Everett, M.G., and Johnson, J.C. 2013. Analyzing Social Networks. Los Angeles: Sage.
Brughmans, T. 2013. Thinking through Networks: A Review of Formal Network Methods in Archaeology. Journal of Archaeological Method and Theory 20 (4): 623–662. https://doi.org/10.1007/s10816-012-9133-8.
Brughmans, T. 2021. Evaluating the potential of computational modelling for informing debates on Roman economic integration. In: Koenraad Verboven (ed.), Complexity Economics: Building a New Approach to Ancient Economic History: 105–123. Cham: Palgrave Macmillan. https://doi.org/10.1007/978-3-030-47898-8_4.
Brughmans, T., Collar, A., and Coward, F. (eds.). 2016. The Connected Past: Challenges to Network Studies in Archaeology and History. Oxford: Oxford University Press. https://doi.org/10.1093/oso/9780198748519.001.0001.
Collar, A., Coward, F., Brughmans, T., and Mills, B.J. 2015. Networks in Archaeology: Phenomena, Abstraction, Representation. Journal of Archaeological Method and Theory 22: 1–32. https://doi.org/10.1007/s10816-014-9235-6.
Costa, J. 2021. Working Paper 35: Social Network Analysis Applied to Illegal Wildlife Trade between East Africa and Southeast Asia. https://baselgovernance.org/publications/SNA_IWT [last accessed 2022-08-26].
Carreras, C., De Soto, P., and Munoz, A. 2019. Land Transport in Mountainous Regions in the Roman Empire: Network Analysis in the Case of the Alps and Pyrenees. Journal of Archaeological Science: Reports 25: 280–293. https://doi.org/10.1016/j.jasrep.2019.04.011.
Cline, D., and Cline, E. 2015. Text Messages, Tablets, and Social Networks: The “Small World” of the Amarna Letters. In: Mynářová, J., Onderka, P., and Pavúk, P. (eds.), There and Back Again—The Crossroads II: 17–44. Prague: Charles University.
Crabtree, S.A., and Borck, L. 2019. Social Networks for Archaeological Research. In: Encyclopedia of Global Archaeology: 1–12. Cham: Springer. https://doi.org/10.1007/978-3-319-51726-1_2631-2.
De Valeriola, S. 2021. Can Historians Trust Centrality? Historical Network Analysis and Centrality Metrics Robustness. Journal of Historical Network Research 6 (1): 85–125. https://doi.org/10.25517/jhnr.v6i1.105.
Graham, S. 2006. Networks, Agent-based Models and the Antonine Itineraries: Implications for Roman Archaeology. Journal of Mediterranean Archaeology 19 (1): 45–64. https://doi.org/10.1558/jmea.2006.19.1.45.
Graham, S., Milligan I., and Weingart, S. 2016. Exploring Big Historical Data: The Historian’s Macroscope. London: Imperial College Press.
Groenhuijzen, M.R., and Verhagen, P. 2016. Testing the Robustness of Local Network Metrics in Research on Archaeological Local Transport Networks. Frontiers in Digital Humanities 3:6. https://doi.org/10.3389/fdigh.2016.00006.
Holland-Lulewicz, J., and Thompson, A.D.R. 2021. Incomplete Histories and Hidden Lives: The Case for Social Network Analysis in Historical Archaeology. International Journal of Historical Archaeology. https://doi.org/10.1007/s10761-021-00638-z.
Knappett, C. (ed.). 2013. Network Analysis in Archaeology: New Approaches to Regional Interaction. Oxford: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199697090.001.0001.
Knappett, C. 2020. Relational Concepts and Challenges to Network Analysis in Social Archaeology. In: Donnellan, L. (ed.), Archaeological Networks and Social Interaction: 20–37. Routledge.
Lemercier, C. 2012. Formale Methoden der Netzwerkanalyse in den Geschichtswissenschaften: Warum und Wie? Österreichische Zeitschrift Für Geschichtswissenschaft 23 (1): 16–41. https://doi.org/10.25365/oezg-2012-23-1-2.
Lewis, J. 2021. Probabilistic Modelling for Incorporating Uncertainty in Least Cost Path Results: A Postdictive Roman Road Case Study. Journal of Archaeological Method and Theory 28 (3): 911–924. https://doi.org/10.1007/s10816-021-09522-w.
Peeples, M.A. 2019. Finding a Place for Networks in Archaeology. Journal of Archaeological Research 27 (4): 451–499. https://doi.org/10.1007/s10814-019-09127-8.
Rollinger, C. 2020. Prolegomena. Problems and Perspectives of Historical Network Research and Ancient History. Journal of Historical Network Research 4: 1–35. https://doi.org/10.25517/jhnr.v4i0.72.
Ryan, Y.C., and Ahnert, S.E. 2021. The Measure of the Archive: The Robustness of Network Analysis in Early Modern Correspondence. Journal of Cultural Analytics 6 (3): 57–88. https://doi.org/10.22148/001c.25943.
Scott, J. 2017. Social Network Analysis. 4th ed. Los Angeles: Sage.
Tsai, F.C., Hsu, M.C, Chen, C.T., and Kao, D.Y. 2019. Exploring Drug-related Crimes with Social Network Analysis. Procedia Computer Science 159: 1907-1917. https://doi.org/10.1016/J.procs.2019.09.363.
Tsirogiannis, C., and Tsirogiannis, C. 2016. Uncovering the Hidden Routes: Algorithms for Identifying Paths and Missing Links in Trade Networks. In: Brughmans, T., Collar, A., and Coward, F. (eds.), The Connected Past: Challenges to Network Studies in Archaeology and History: 103-120. Oxford: Oxford University Press. https://doi.org/10.1093/9780198748519.003.0012.
Verhagen, P. 2018. Spatial Analysis in Archaeology: Moving into New Territories. In: Siart, C., Forbriger, M., and Bubenzer, O. (eds.), Digital Geoarchaeology. Natural Science in Archaeology: 11–25. Cham: Springer. https://doi.org/10.1007/978-3-319-25316-9_2.
Verhagen, P., Nuninger, L., and Groenhuijzen, M.R., 2019. Modelling of Pathways and Movement Networks in Archaeology: An Overview of Current Approaches. In: Verhagen, P., Joyce, J., and Groenhuijzen, M. (eds.), Finding the Limits of the Limes. Computational Social Sciences: 217–249. Computational Social Sciences. https://doi.org/10.1007/978-3-030-04576-0_11.
Vivrette, A.T. 2022. Approach to the Global Human Trafficking Crisis: Analyzing Applications of Social Network Analysis. PhD Dissertation. http://hdl.handle.net/1803/17435 [last accessed 2022-08-26].
Wasserman, S., and Faust, K. 1994. Social Network Analysis. Methods and Applications. Structural Analysis in the Social Sciences 8. Cambridge: Cambridge University Press.
Cited Network Analytical Software:
-The Vistorian (https://vistorian.net/)
Communities and Blogs of Archaeological and Historical Network Researchers:
-The Connected Past (https://connectedpast.net/)
-Historical Network Research (https://historicalnetworkresearch.org/)
-Archaeological Networks (https://archaeologicalnetworks.wordpress.com/)
S33. Bayesian Inference in Archaeology: new applications and challenges
Simon Carrignon, McDonald Instittute for Archaeological Research, University of Cambridge
Alfredo Cortell-Nicolau, University of Cambridge
Enrico Crema, University of Cambridge
Christian Sommer, Universität Tübingen
Session type: Standard
The archaeological record provides a unique opportunity to study past human behaviour . Its record, nonetheless, is not straightforward to analyse — it is scarce, noisy, biased, incomplete and unevenly distributed over space and time. Bayesian statistics offers a inferential framework that is well suited for tackling these problems, offering ways to quantify uncertainties arising from these limitations and providing means to take them into account when drawing our conclusions. Bayesian inference has made great advances recently. While initial applications in archaeology were limited within the confines of chronological modelling and few dedicated softwares packages (e.f. OxCal and BCal). The last decade saw a major change – with applications including faunal analyses, diet reconstructions, paleodemography, past economy, and cultural evolution to name a few examples. This major change in archaeological practice was made possible thanks to the increased computational power of desktop machines , a the availability of a large number of probabilistic programing languages (e.g. JAGS, Stan, Nimble,etc.) , a growing number of “hands-on” literature on Bayesian methods (McElreath 2020), and the increased number of scholars across disciplines sharing their scripts and code to ensure their work is fully transparent and reproducible..
With this session we want to capture this momentum by proposing a showcase of how archaeologists face their own specific problems using formal inference and probability theory, but also a broader reflection of where we are and where can we go using these types of techniques. In order to do so, we raise a series of questions:
- How can Bayesian statistics and probability theory help understanding the archaeological record?
- What are the specific archaeological challenges in applying techniques designed to handle measurement error and missing data?
- What probabilistic methods can/are being applied within archaeology?
- What are the specific challenges in re-using inferential models developed in other fields within archaeology?
By bringing together archeologists who already apply Bayesian inferential techniques to their work or are interested to do so, we hope to increase the awareness and visibility of such methods in the larger field of archaeology. By showcasing successful examples of application of probabilistic inference in archaeology, we hope to convince people of the power of such an approach. Finally, we also want to offer a platform where researchers using Bayesian approaches can share knowledge and keep themselves up to date with the latest techniques in use.
We invite proposals of any applications of Bayesian statistics in archaeology, with particular interest in the following areas:
- Hierarchical Modelling
- Gaussian Process Modelling in Spatial and Temporal Analyses
- Bayesian Networks
- Phylogeography and phylogenetic Analyses
- Inference with missing Data and measurement errors
- Mixture Models
- Likelihood-free methods (e.g. Approximate Bayesian Computation, Bayesian Synthetic Likelihood)
The session is not limited to any chronology or geographical area and may include case studies, theoretical reflections, methodological innovation and assessment, etc. Innovative approaches and novel insights are particularly welcome as well as students and early career researchers who want to present preliminary results.
McElreath, R. (2020). Statistical Rethinking: A Bayesian Course with Examples in R and Stan. CRC Press, Boca Raton.
S34. Computational Approaches and Remote Sensing Applications in Desertic Areas
Alessia Brucato, University of Bari Aldo Moro (UNIBA) and Institute of Heritage Science, National Research Council of Italy (ISPC – CNR)
Giulio Lucarini, Institute of Heritage Science, National Research Council of Italy (ISPC – CNR)
Nicola Masini, Institute of Heritage Science, National Research Council of Italy (ISPC – CNR)
Giuseppe Scardozzi, Institute of Heritage Science, National Research Council of Italy (ISPC – CNR)
Session type: Standard
Past natural and human activities have left marks on the landscape of every type of environment on the surface of our planet. These can be recognized even after millennia; they can be ephemeral or clearly apparent. Their visibility is dependent on the time passed and the natural or human activities that took place over time, but many of them can be detected via remote sensing techniques. Arid environments often experience strong dusty winds and a continuous movement of dunes or soil particles. These conditions can quickly and entirely cover (or preserve) historical and paleo-environmental remains, creating an obstacle to ground surveys, and a hindrance to some remote sensing techniques. Remote sensing methods focusing on far distance optical, radar and multispectral scanning, allow researchers to overcome these obstacles, providing valuable information about modern and ancient geomorphological, hydrographical, environmental, and archaeological evidence. In the past few decades, many arid areas of our planet have been scanned via various remote sensing methods, and many of the images are in open access repositories, meaning that there is a wealth of information freely available. Archaeological studies initially focused on the analysis of space photos coming from declassified spy satellites (Corona and Hexagon) and optical imagery from Landsat, SPOT, and ASTER missions. This was followed by work on Very High Resolution (VHR) imagery from Ikonos-2, QuickBird-2, GeoEye-1, WorldView-1/2/3/4, Pléiades-1A/1B and Pléiades Neo missions. These images offered unparalleled resources to the manual detection and analysis of the archaeological sites. Recently, UAV photography, 3D modelling, and free commercial optical satellite and aerial imagery provided by web map service such as Google Earth and Bing Maps has opened up new avenues of research. Satellite radar imagery (as opposed to photographs) coming from SIR-A/B/C, AIRSAR and SRTM SAR or 2nd generation multi-bands SAR systems such as ALOS PALSAR, TerraSAR-X/TanDEM-X, COSMO-SkyMed and Radarsat-2 or aerial/UAV LiDAR scans that penetrate the superficial covering layers and reach the historical traces have been invaluable. Archaeologists have now also started to exploit the resources coming from multi-spectral (and soon hyper-spectral) satellite missions like Sentinel 2 to detect or monitor historical features via their spectral signatures. All this information was (and usually is still), processed through a variety of manual techniques, enhancing archaeological marks and proxy indicators, and post-processed via various human operators analyses and protocols. Recently, many new automatic supervised and unsupervised computational approaches (Filters, Machine and Deep Learning algorithms, AI, etc.) have added powerful new tools and workflows to the thematic interpretation of images with considerable savings in the processing time. The results of all these studies have already enabled archaeologists to detect many new archaeological sites and paleo-environmental features. This facilitates the monitoring and measurement of conservation risks of endangered historical sites, and the unveiling of ancient pathways, hydrological features, and settlements. All of this contributes to the planning of effective conservation strategies and study and re-use of hidden resources, in collaboration with local and international authorities. The session we are proposing will focus discussion on the results coming from studies relating to the usage of aerial/UAV/satellite remote sensing resources; manual and automatic computational workflows of image analysis; and the limitations and opportunities of these techniques applied in desertic and arid contexts for the aforementioned purposes. We therefore encourage the submission of papers that highlight innovative remote-based archaeological applications in desertic areas, following or proposing similar topics:
- Use of multi-petabyte repositories of geospatial datasets in arid environment
- Remote sensing analysis of large areas or landscape analyses over time-series in arid environments
- Application of complex computing, cloud-based computing, or multiplatform workflows to overcome archaeological remote sensing problems in desertic areas
- Geospatial data processing and post-processing via manual procedures (Analysts training, Analyses Protocols, Database, etc.) and automatic/semi-automatic approaches (Filters, Machine Learning and Deep Learning algorithms, AI, etc.) in arid environments
- Joint or integrated use of optical, multispectral and radar satellite imagery
- Derivative works coming from remote sensing and computational analyses to study, monitor and preserve historical contexts or plan future activities in desertic region in agreement with local, international, public or research institutions
Amani M., Ghorbanian A., Ahmadi S.A., Kakooei M., Moghimi A., Mirmazloumi S.M., Moghaddam S.H.A., Mahdavi S., Ghahremanloo M., Parsian S., Wu Q., Brisco B. 2020. Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review, in IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 13
Casana J., 2014. Regional scale archaeological remote sensing in the age of big data. Automated site discovery vs. brute force methods in Advance in Archaeological Practice, 2(3), 222233. doi: 10.7183/232637184.108.40.206
Costanzo S., Brandolini F., Idriss Ahmed H., Zerboni A., Manzo A. 2021. Creating the funerary landscape of Eastern Sudan, in PLoSONE, July 7 2021, 16(7):e0253511, doi: https://doi.org/10.1371/journal.pone.0253511
Di Giacomo G., Scardozzi G. 2012. Multitemporal High-Resolution Satellite Images for the Study and Monitoring of an Ancient Mesopotamian City and its Surrounding Landscape: The Case of Ur, in International Journal of Geophysics, 2012, ID 716296, doi: 10.1155/2012/716296
Fabiani U., Lucarini G. 2010. Spatial research and geomatic resources applied to the archaeology of the Farafra Oasis (Western Desert, Egypt), in Rivista di scienze preistoriche, LX, 2010, pp. 331-347
Gauthier Y., Gauthier C. 2008. Monuments en trou de serrure, monuments à alignement, monuments en “V” et croissants: contribution à l’étude des populations sahariennes, in Cahiers de l’AARS, 12, 2008, pp. 1-20
Gauthier Y., Gauthier C. 2017. Monuments funéraires sahariens et aires culturelles, in Les Cahiers de l’AARS, 11, 2007
Harrower M.J., Schuetter J., Mccorriston J., Goel P.K., Senn M.J. 2013. Survey, Automated Detection, and Spatial Distribution Analysis of Cairn Tombs in Ancient Southern Arabia. In Mapping Archaeological Landscapes from Space, in Mapping Archaeological Landscapes from Space 2013, 259268, doi:10.1007/9781461460749_22
Kvamme K., 2020. Automated Archaeological Feature Detection Using Deep Learning on Optical UAV Imagery: Preliminary Results; Bevan, in Computational Approaches to Archaeological Spaces, 2020, pp. 53-68
Lasaponara R., Masini N. 2013. Satellite Synthetic Aperture Radar in Archaeology and Cultural Landscape: An Overview, in Archaeological Prospection, 20:71-78, 2013, doi: 10.1002/arp.1452
Lasaponara R., Masini N. 2018. Space‑Based Identification of Archaeological Illegal Excavations and a New Automatic Method for Looting Feature Extraction in Desert Areas, in Surveys in Geophysics, 39, 2018, pp. 1323–1346
Lasaponara R., Masini N. 2019. Active Satellite Sensors in Cultural Heritage Research. The Use of SAR for Archaeological Prospection, in Remote Sensing for Archaeology and Cultural Landscapes, Best Practices and Perspectives Across Europe and the Middle East, 2019, DOI: https://doi.org/10.1007/978-3-030-10979-0_7
Masini N., Lasaponara R. 2019. Recent and Past Archaeological Looting by Satellite Remote Sensing: Approach and Application in Syria, in Remote Sensing for Archaeology and Cultural Landscapes, 2019, doi: https://doi.org/10.1007/978-3-030-10979-0_8
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
Orengo H.A., Conesa F.C., Garcia-Molsosa A., Lobo A., Green A.S., Madella M., Petrie C.A. 2020. Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data, in Proceedings of the National Academy of Science of the United States of America, PNAS 2020, 117, 31, 2020, pp. 18240-18250
Rayne L., Gatto M.C., Abdulaati L., Al-Haddad M., Sterry M., Sheldrick N., Mattingly D. 2020. Detecting Change at Archaeological Sites in North Africa Using Open-Source Satellite Imagery, in Remote Sensing, 12, 22, 2694
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
Scardozzi G. 2010. Multitemporal satellite high resolution images for the knowledge and the monitoring of the Iraqi archaeological sites: the case of Seleucia on the Tigris, in Photo Interpretation. European Journal of Applied Remote Sensing, 4, 2010, pp. 143-160
Scardozzi G. 2011. Multitemporal Satellite Images for Knowledge of the Assyrian Capital Cities and for Monitoring Landscape Transformations in the Upper Course of Tigris River, in International Journal of Geophysics, 2011, ID 917306, doi: 10.1155/2011/917306
Tapete D., Cigna F., Donoghue D.N.M. 2016. Looting marks’ in space borne SAR imagery: Measuring rates of archaeological looting in Apamea (Syria) with TerraSARX Staring Spotlight, in Remote Sensing of Environment, 178, 42581
S35. Indigenous Knowledge and Digital Archaeology: potential, problems and prospects
Eleftheria Paliou, University of Cologne
Patricia Murrieta Flores, Lancaster University
Session type: Standard
To date, several research projects have sought to establish collaborations between indigenous communities and archaeologists. Such works have drawn attention to the benefits but also the challenges of combining archaeological theory and methods, including digital and computational methods, with indigenous worldviews. On one hand, the use of digital technologies in archaeological projects engaging indigenous communities has offered new possibilities for the preservation, management and interpretation of archaeological heritage and valuable insights into critical and widely debated themes in archaeological and anthropological research (Raichlen et al. 2014; Wood et al. 2021). At the same time, interactions between local communities and digital archaeology experts have opened up new opportunities for reciprocal knowledge transfer, and, in some cases, the economic sustainability of indigenous groups. Nonetheless, the use of digital methods in indigenous archaeology and heritage has also raised a number of issues with respect to the imposition of colonial practices and frameworks, ethical conduct in scientific practice, and equitable participation in data governance (management, ownership, accessibility) and knowledge production (Gupta et al. 2020; Sanger and Barnett 2022). This session invites papers that discuss the potential and challenges of using digital tools and methods in collaborative research between archaeologists and indigenous communities. We especially encourage contributions that focus upon (1) the experiences and benefits of interacting with indigenous communities to advance digital archaeological research and computational modelling, (2) the integration of indigenous knowledge systems into data capture, digitisation, dissemination, and analysis and (3) the ways in which digital archaeology can support the economic sustainability of indigenous groups and empower indigenous communities to investigate and communicate their past.
We are also interested more broadly in papers exploring synergies between indigenous knowledge and digital archaeology, and contributions that discuss ethical considerations related to the participation of indigenous communities in digital archaeological research.
Neha Gupta, Sue Blair & Ramona Nicholas (2020) What We See, What We Don’t See: Data Governance, Archaeological Spatial Databases and the Rights of Indigenous Peoples in an Age of Big Data, Journal of Field Archaeology, 45:sup1, S39-S50, DOI: 10.1080/00934690.2020.1713969
Raichlen, David A., et al. (2014) “Evidence of Lévy walk foraging patterns in human hunter–gatherers.”Proceedings of the National Academy of Sciences 111.2: 728-733.
Sanger,M., & Barnett, K. (2021). Remote Sensing and Indigenous Communities: Challenges and Opportunities. Advances in Archaeological Practice, 9(3), 194-201. doi:10.1017/aap.2021.19
Wood, B., Harris, J., Raichlen, D., Pontzer, H., Sayre, K., Sancilio, A., Berbesque, C., Crittenden, A., Mabulla, A., McElreath, R., Cashdan, E., and Jones, J.H. (2021) “Gendered movement ecology and landscape use in Hadza hunter-gatherers” Nature Human Behaviour 5 (4), 436-446.
S36. Where do you go to my lovely? From punch card technology to Deep Learning. Tracing the development of statistical thinking in(to Computational) Archaeology
Agnes Schneider Faculty of Archaeology University of Leiden And Historical Building Research Technical University Berlin
Gail Higginbottom Incipit, Spanish National Research Council (CSIC)
Maria-Elan Castiello Institut für Archäologische Wissenschaften University of Bern
Session type: Standard
Archaeology produces and deals with information collected and created by archaeologists. Just as there are many Archaeologies, there are also many ways to collect, interpret and analyse data and many approaches to archaeological thinking.
The use of statistical methods in Archaeology reaches back to the end of the 19th century (Petrie 1899) and became computer-based after the middle of the 20th century. The first applications of statistical-mathematical methods using computers transformed the handling of spatial and quantitative data (e.g. Goldmann 1979) and the view on Archaeology itself (e.g. Clarke 1968; Hodder and Orton 1976; Ihm and Zimmermann 1978) which facilitated the use and combinations of diverse data sources. This quantitative-statistical analytical view prepared archaeologists for the advent of publicly available, high-resolution digital data, which revolutionised and broadened Archaeology.
Through time, statistical approaches were adopted for a broad range of spatial analyses. The most impactful methods were applied on landscape scale, such as the conversion of paper map data to digital elevation data (e.g. by the Ordnance Survey of UK), along with the evolution of mapping itself. From this developed Landscape Archaeology, which adopted the use of remote sensing data, branching into a whole new discipline: Archaeological Remote Sensing (ARS). The new data sources, including geophysical platforms, led to the need for handling big spatial data and thence to the specialised use of GIS platforms (O’Sullivan and Unwin 2010; Wheatley 2004). The development and application of methods such as predictive modelling (Leusen and Kamermans 2005; Kamermans et al. 2009), along with the early realisation of the importance of sampling and the use of statistics (Banning 2020 in Gillings et al. 2020), followed. Such large amounts of detailed data have led the quest across real landscapes requiring the use and/or development of appropriate statistics (Lloyd &Atkinson 2020 in Gillings et al. 2020). These large individual ‘scapes’ became the bases for broad, cross-area relationship studies, representing human interaction.
For most areas of archaeology there has been a hand-in-hand development of scientific tools and statistical analyses. ARS has seen the sophistication of airborne platforms, sensors and imaging technologies, like LiDAR, hyper-spectral imagery and drone derived imagery (Agapiou and Lysandrou 2015; Luo et al. 2019)which have helped the diversification of this sub-discipline’s toolset. Such technical developments continuously push specialists to look for, borrow and adapt methods to analyse big data. We see machine learning (ML) as automated statistics becoming a common method for archaeological analysis, particularly in Landscape Archaeology (Orengo et al. 2021; Verschoof-van der Vaart and Lambers 2019). With significant developments in the last few years, ML has rapidly gained importance and is not likely to diminish in the foreseeable future. Although Automated ARS is still in its infancy (Opitz and Herrmann 2018), the use of scripting languages (Carlson 2017) and FAIR principles (also in other Archaeologies) point also towards a promising future.
This review brings to the fore some major statistical developments in archaeology, and despite its impact and heavy use in archaeology today, we have noticed that sessions dedicated to statistics rarely occur at the CAA in more recent times. Therefore, for the 50th anniversary of the CAA, this session would like to critically reflect on lessons learnt in the past or investigate the importance of statistical thinking today in Archaeology.
The main question we ask is: are we there yet?
Enfolded in this main enquiry are the following issues: are we heading in the right direction? Are we using the tools in the right way: have either qualitative or quantitative statistics let down researchers by misleading or confirming an archaeological ‘truth’ in the past that has since been overturned due to new data or approaches (Bergh et al. 2021)? Models and predictions are great tools – but where do the pitfalls lie? So, as archaeologists, are we mostly misled by the theory of statistics concerning the actual application? How to bridge the gap?
We request successful and cautionary tales to disseminate this topic and point to possible directions to counter this. Have we found “the” solutions to old questions with the ever renewing tool boxes or are we always facing new questions? Do we have standardised/formalised methods for specific problems? Do we use all tools available to also communicate and disseminate research for others to build upon? Are our methods FAIR and reproducible ? If so, or not, why (not)(Berberi and Roche 2022)? What should we be doing about it?
So, ARE, we there yet? We invite the CAA community to consider and discuss the relevance of statistical thinking and application in Archaeology in the past, today and in the future.
Agapiou, A., and Vasiliki L. 2015. ‘Remote Sensing Archaeology: Tracking and Mapping Evolution in European Scientific Literature from 1999 to 2015’. JAS: Reports 4 (December): 192–200. https://doi.org/10.1016/j.jasrep.2015.09.010.
Berberi, I., and Roche, D.G., 2022. No evidence that mandatory open data policies increase
error correction. Nat Ecol Evol 1–4. https://doi.org/10.1038/s41559-022-01879-9
Bergh, D. van den, Clyde, M.A., Gupta, A.R.K.N., de Jong, T., Gronau, Q.F., Marsman, M., Ly,
A., Wagenmakers, E.-J. 2021. A tutorial on Bayesian multi-model linear regression with
BAS and JASP. Behav Res 53, 2351–2371. https://doi.org/10.3758/s13428-021-01552-2
Carlson, D. L. 2017. Quantitative Methods in Archaeology Using R. CMA. Cambridge: CUP. https://doi.org/10.1017/9781139628730.
Clarke, D. L. 1968. Analytical Archaeology. London: Methuen.
Gillings, M., P., Hacıgüzeller, and Lock, G. (eds.) 2020. Archaeological Spatial Analysis. London: Routledge. https://doi.org/10.4324/9781351243858.
Goldmann, K., 1979. Die Seriation chronologischer Leitfunde der Bronzezeit Europas, Berliner
Beiträge zur Vor- und Frühgeschichte ; n.F., Bd. 1. Berlin: Spiess.
Ihm, P., Zimmermann, A., 1978. Statistik in der Archäologie : Probleme d. Anwendung, allg.
Methoden, Seriation u. Klassifikation, Archaeo-physika ; Bd. 9. Bonn: Habelt.
Hodder, I., and Clive O. 1976. Spatial Analysis in Archaeology. New Studies in Archaeology 1. Cambridge; NYk: CUP. https://catalogue.nla.gov.au/Record/1575236.
Kamermans, H., M. van Leusen, and Verhagen, J. W. H. P. (eds.) 2009. Archaeological Prediction and Risk Management. Archaeological Studies Leiden University 17. LEIhttps://research.vu.nl/en/publications/archaeological-prediction-and-risk-management-alternatives-to-cur.
O`Sullivan, D., and Unwin, J.D. 2010. Geographic Information Analysis. 2nd Edition. https://www.wiley.com/en-us/Geographic+Information+Analysis%2C+2nd+Edition-p-9780470288573.
Opitz, R., and Jason H. 2018. ‘Recent Trends and Long-Standing Problems in Archaeological Remote Sensing’. JCAA 1 (1): 19–41. https://doi.org/10.5334/jcaa.11.
Orengo, H. A., Garcia-Molsosa, A., Berganzo-Besga, I., Landauer, J., Aliende, P., and Tres-Martínez, S. 2021. ‘New Developments in Drone-Based Automated Surface Survey: Towards a Functional and Effective Survey System’. AP n/a. https://doi.org/10.1002/arp.1822.
Petrie, F. W. 1899. ‘Sequences in Prehistoric Remains’. JAI 29, 295-301.
Verschoof-van der Vaart, W., and Lambers, K. 2019. ‘Learning to Look at LiDAR: The Use of R-CNN in the Automated Detection of Archaeological Objects in LiDAR Data from the Netherlands’. JCAA 2 (1): 31–40. https://doi.org/10.5334/jcaa.32.
S37. Modelling the semantics of space – the relationship of entities creating space
Aline Deicke, Philipps-University Marburg
Asuman Lätzer-Lasar, Philipps-University Marburg
Sarah Pittroff, Academy of Sciences and Literature | Mainz
Session type: Standard
Over the past 50 years, digital archaeology has made enormous progress in unlocking the potential of computational approaches for the study of the human past. Particularly the application of quantitative methods on archaeological research topics has been quite extensively researched and conducted with immense success. Yet, in light of a growing awareness of the supposed objectivity of numbers and so called hard facts, ways of conceptualising, analysing and interpreting archaeological data using qualitative methods and theories have come into focus – on their own as well as in their interplay with quantitative approaches. The challenges of the fragmentary nature of the material record, the vagueness and the uncertainty implicit in data of the past, pose particular risks in archaeology and ancient history that yet also offer rich potential: Especially with increasingly interdisciplinary research tendencies, the combination and entanglement of quantitative studies with in-depth critical perspectives on the complexities of micro as well as macro patterns through the soft facts will open up this data to new and innovative avenues of research.This session aims at bringing the intangible data and approaches, techniques or applications using qualitative data into the spotlight. The extension of a quantitative focus with qualitative perspectives becomes especially evident in a field of research central to all archaeological disciplines: The study of space. Archaeology as a discipline relies primarily on three-dimensional data of spaces and objects that is very often expressed in quantitative measurements, be it length, volume or coordinates. For this reason, historically the use of analytical techniques that specifically investigate the constitution, development and shape of physical environments and/or assemblages (down to the decayed human body) are usually in the centre of attention. Apart from widely used tools – for example GIS software – and the research paradigms they embody, this focus becomes evident as early as in the data modelling stages of research processes. For example, the spatial relations as codified by the CIDOC CRM do not allow for detailed description of the interactions between actors and places nor for more complex perspectives on the spatial relations between objects that extend its – at heart – positional approach (Bekiari et al. 2022, xxii–xxiv). However, as early as the 1960s, processual archaeologists understood that the measured, physical environment was not sufficient for investigating ancient societies. As a first attempt to circumvent the problem, they extended the concept of landscape in a new way by including qualitative data, such as semantics or symbolism, into their research. At the same time, sociologists like Lefebvre (1974) redefined the concept of spatiality, which in their understanding was the outcome of social relations independent of the actor´s social class. In the 1990s, further work conceptualised organisational structures in the context of space, a movement that was shaped especially by Martina Löw’s work “Raumsoziologie” (Sociology of Space; Löw 2001). This perspective, which entered cultural studies as the so-called spatial turn, enabled researchers to study (past) societies in their holistic complexity and, above all, free from hierarchical, mostly elite-oriented models of society. Nowadays, such relational models of space that are able to speak about intention and reception in the constitution of space as well as social action rather than mere construction have found wide acceptance and usage in most fields of the humanities (Werlen 1993). In the archaeological disciplines, space as a witness of social organisation can contribute to a broader and multi-faceted understanding of our cultural heritage. While, every so often, these theories and concepts have found their way into archaeological research (e.g. Gramsch/Meier 2013, Maran 2004/05, Thaler 2044/05), their translation into specifically digital archaeology still seems to be in its infancy. This opens up a wide field for digital archaeology which has not sufficiently spread in our discipline: How can we conceptualise data models that prioritise the construction of social entanglements in their envisioning of space and spatial relations? How can we enable interoperability between such models and which aspects would this interoperability even address? How can we open up these qualitative approaches to quantitative analyses such as network research or ontology engineering, and how can we include the critical perspective necessary to interpret the results in this process? With this session, we focus on these and many other questions on computational approaches along all stages of the research process. Therefore, the session is open to all contributions concerning digital approaches to space as a social construct in archaeology and its related fields, ranging from conceptual models to analytical tools and methods to the development and applications of software, and many more. We welcome papers from any academic stage and encourage especially students and junior researchers to present their work, even if in progress. We are also very keen to receive abstracts from established scholars who may share the pitfalls and risks in integrating qualitative data into the evaluation of past societies.
Bekiari, Chryssoula, George Bruseker, Martin Doerr, Ore Christian-Emil, Stead Stephen, Athanasios Velios, Erin Canning, and Philippe Michon. 2022. Volume A: Definition of the CIDOC Conceptual Reference Model. Version 7.2.1. ICOM/CIDOC Documentation Standards Group/CRM Special Interest Group. http://www.cidoc-crm.org/sites/default/files/CIDOC%20CRM_v.7.0_%2020-6-2020.pdf.
de Certeau, Michel. 1984. The Practice of Everyday Life. Berkeley: University of California Press.
Gramsch, Alexander, and Thomas Meier. 2013. “An Archaeological Outline of Ritual Dynamics and Social Space.” In Counterpoint. Essays in Archaeology and Heritage Studies in Honour of Professor Kristian Kristiansen, edited by Sophie Bergerbrant and Serena Sabatini, 193–98. BAR 2508. Oxford: Archaeopress.
Lefebvre, Henri. 1974. La Production de l’espace. Paris: Éditions Anthropos.
Löw, Martina. 2001. Raumsoziologie. Frankfurt a.M.: Suhrkamp.
Maran, Joseph. 2004. “Architektur als gesellschaftlicher Raum. Zur Bedeutung sozialwissenschaftlicher Theorien für die Archäologie.” Online-Publication. Heidelberg. https://www.uni-heidelberg.de/fakultaeten/philosophie/zaw/akh/akh_texte/texte0405.html.
Thaler, Ulrich. 2004. “Space-Syntax-Analyse der mykenischen Residenz von Ano Englianos.” Online-Publication. Heidelberg. https://www.uni-heidelberg.de/fakultaeten/philosophie/zaw/akh/akh_texte/texte0405.html.
Werlen, Benno. 1993. Society, Action and Space: An Alternative Human Geography. London: Routledge.
S38. Computational Modeling Water-Based Movement
Emma Slayton, Carnegie Mellon University
Session type: Standard
Computational Modeling Water-Based Movement This session invites members of the Computational Modeling Water-Based Movement Special Interest Group, and those with similar interests and research foci, to present updates on their work. As this computational archaeological focus is still developing (excitingly with an increasing number of papers at CAA every year), many researchers still have their own singular methods, applications, and algorithms to discuss past mobility practices. Despite the presence of several publications on these themes (see bibliography), there are still those just starting in this work who are unaware of our developing community, or researchers who are deeply involved in this type of modeling who are not connected with other corners of the community due to a difference in the focus of region or time period. Scholars researching similar questions are often unaware of one another’s work and theoretical underpinnings, which in turn can lead to the re-invention of the wheel, duplicated projects, and individuals needlessly struggling to overcome challenges that have been tackled and solved by other researchers. Having researchers learn about what else is happening in the field can only serve to broaden the capabilities of our work as a whole. For example, where different approaches have been applied to address similar topics we can learn from each other’s successes and failures. Many researchers have explored Agent Based Modeling approaches in similar areas to where deterministic pathway analysis has been used, with different climate data as the base (e.x. Smith 2020 and Litvine 2022), helping to point out the benefits of each approach. On the flip side, we have several researchers using the same approach in the same region (e.x. Blakley 2018 and Poullis et al 2019), but with different results that can help researchers judge the fidelity of different projects. Recent efforts to combat the siloing of researchers include the creation of the CAA Special interest group sharing the name of this session, as well as several other sessions and roundtables at past conferences (e.g. Kyriakidis et al. 2022; Slayton et al. 2022). In addition, this session seeks to build off outcomes of the CAST conference held at Stanford in 2022. In the spirit of these past sessions, and newly concentrated interest modeling water-based mobility in the past using computational means, this session seeks to further develop this community. We hope to bring together researchers from multiple corners of this discussion, including but not limited to computational archeology, anthropology, oceanography, atmospheric sciences, geography, and computer science. We encourage our colleagues working in this area to submit paper on various aspects of modeling movement across water including (but not limited) to: Case studies exploring seafaring and voyaging using computational methods Case studies exploring coastal environments using computational methods Use of water modeling as outreach (e.g. computer games, VR experiences) Evaluation of theory employed to add context to computationally modeling water based mobility Issues facing the field of water movement modeling Finding, using, and maintaining climate data sets for use in modeling Through this session we hope presenters will explore and showcase various approaches to analyzing and researching maritime spaces. We also hope this session brings together researchers who participate in maritime digital archeology, so as to further develop participation and interest in the Computational Modeling Water-Based Movement Special Interest Group. If you have any questions or would like to join the special interest group, contact firstname.lastname@example.org.
Litvine, A, Lewis, J., and Starzec, A. (2022) CAA Oxford. Session 27. Modelling prehistoric maritime mobility. Paper 98. Where did the ships sail? Simulating European shipping routes before the age of steam.
Blakely, S. (2018). Sailing with the Gods: serious games in an ancient sea. thersites. Journal for Transcultural Presences & Diachronic Identities from Antiquity to Date, 7.
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.
Kyriakidis, P., Gravanis, E., Demesticha, S., Reepmeyer, C. Moutsiou, T., Bar-Yosef, B., Chliaoutakis, A., Zervakis, H., Theodorou, K., Xoplaki, E., and Montello, D. (2022) CAA Oxford. Session 27. Modelling prehistoric maritime mobility 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.
Leidwanger, J., & Knappett, C. (2018). Maritime networks, connectivity, and mobility in the ancient Mediterranean. Maritime networks in the ancient Mediterranean world, 1-21.
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.
Poullis, C., Kersten-Oertel, M., Benjamin, J. P., Philbin-Briscoe, O., Simon, B., Perissiou, D., … & Rizvic, S. (2019). Evaluation of “The Seafarers”: A serious game on seaborne trade in the Mediterranean Sea during the Classical period. Digital Applications in Archaeology and Cultural Heritage, 12, e00090.
El Safadi, C. (2018). The maritime world of the early Bronze Age Levant through space and time (Doctoral dissertation, University of Southampton).
Smith, K. (2020). Modelling Seafaring in Iron Age Atlantic Europe. PhD Dissertation, University of Oxford: Oxford.
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.
Slayton, E, Borreggine, J. Farr, R. H., Jarriel, K., Leidwanger, J., El Safadi, C., Davies, B., and Smith, K. (2022) CAA Oxford. Session 23. Computational archaeology and seafaring theory.
S39. Web-database solutions for the excavation datasets
Paweł Lech, Polish Centre of Mediterranean Archaeology, University of Warsaw
Wojciech Ostrowski, The Faculty of Geodesy and Cartography, Warsaw University of Technology
Łukasz Miszk, Polish Centre of Mediterranean Archaeology, University of Warsaw
Session type: Standard
Contemporary field archaeology can be characterised as a rush into use more and more digital research methods. The consequence of this is the collection of a wide variety of data: beginning with digitised paper documentation, through spreadsheets such as Excel, Access, photographs and drawings, to very specialised data such as 3D models, microscopic images, non-invasive prospection data or imagery acquired from a variety of platforms like UAVs or satellites. This diversity and volume of data generate several problems facing modern field archaeologists. These problems can be put into a few key points:
1) The storage of collected data in a single environment, which should allow the active use of this information, both at the fieldwork and study levels.
2) The accessibility of the acquired data so that it can be viewed, edited, or used by as wide an audience as possible, in the first instance by expedition members, more widely by the public.
3) The state of existing database solutions. Many emerging open databases are the result of scientific or development projects, and often after the end of their implementation and amortisation period, such solutions are no longer developed or supported. It causes a decrease in their usability, reliability, and significantly hinders their development. This last problem is especially relevant from the point of view of archaeologists who in such a case have to bear the costs for the maintenance and development of their chosen software.
We would like to ask a question and discuss the following issue: Is the rapid development of web-based data solutions for archaeologists an answer to a growing number of data gathered during excavations and a need for its digitization?
For our session, we would like to invite researchers who could share their experience with implementing and using both commercial and open-source databases based on web-based solutions in their excavation practice. From initial excavation recording, surveys, through advanced studies, post-excavation analysis, research and dissemination or archiving. Both small or time-limited projects and large, long term projects with a complex structure will be a point of interest.
If you are using databases solutions like Arches (The Getty Conservation Institute), Portable Antiquities Scheme (the British Museum and Amgueddfa Cymru – National Museum Wales), Open Atlas, FAIMS (Macquarie University), The Archaeological Recording Kit (ARK), HEURIST (University of Sydney) or any other specially designed web-database, we would like to encourage you to talk about your experiences.
Doerr M.; Theodoridou M., Aspöck E., Masur A., Mapping Archaeological Databases to CIDOC-CRM, [in:] Campana S., Scopigno R., Carpentiero G., Cirillo M. (eds.), Proceedings of the 43rd Conference on Computer Applications and Quantitative Methods in Archaeology Keep The Revolution Going CAA, Siena, Italy, 30 March–2 April 2015, p. 443–452.
Filzwieser R., Eichert S., Towards an Online Database for Archaeological Landscapes. Using the Web Based, Open Source Software OpenAtlas for the Acquisition, Analysis and Dissemination of Archaeological and Historical Data on a Landscape Basis, Heritage 3, p. 1385-1401, 2020.
Mafredas T., Malaperdas G., Archaeological Databases and GIS: Working with Databases, European Journal of Information Technologies and Computer Science 1 (3), p. 1-7, 2021.
Roosevelt C.H., Cobb P., Moss E., Olson B.R., Ünlüsoy S., Excavation is Destruction Digitization: Advances in Archaeological Practice, Journal of Field Archaeology 40 (3), p. 325-346, 2015.
S40. Metaverse, blockchain and NFTs. The state of art in cultural heritage
Daniele Bursich, università degli studi di Salerno
Riccardo Giovanelli, Ca’ Foscari University of Venice, Center for Cultural Heritage Technology – Istituto Italiano di Tecnologia
Session type: Standard
“Metaverse” is a label coined by Neal Setphenson in his cyberpunk sci-fi book “Snow Crash” (1992): it represents a sort of virtual reality shared through the internet, where one is represented in 3D by his own avatar. Today, the recent explosion of the term onto the public scene is due to the combination of a more common technological maturity, the popularity of blockchain-based currencies, the diffusion of free 3D assets as well as the emerging interest in virtual online spaces. With so many iterations and use-cases, the metaverse is tricky to define.
Metaverses have existed for decades as multiplayer online games. Nonetheless, we might soon enter an age of immersive experiences hardly distinguishable from the real world – fostering new modes of interaction for gamers and non-gamers alike. Prototype next-generation metaverses such as “Decentraland” and “Somnium Space” already show the existence of true societies, with individuals settling lands, interacting socially, exchanging goods and asserting ownership rights. Any society (physical or virtual) needs a functional economy: in the metaverse, the economy depends on authentication of digital properties, such as one’s metaverse home, car, farm, books, clothing and furniture. To flourish, it also needs the ability to allow travel and trade freely between realms that might have different laws and rules.
Non-fungible tokens – records of digital ownership stored in the blockchain – will be the linchpin of the metaverse economy, by enabling authentication of possessions, property and even identity. Since each NFT is secured by a cryptographic key that cannot be deleted, copied or destroyed, it enables the robust, decentralised verification – of one’s virtual identity and digital possessions – necessary for metaverse society to succeed and interact with other metaverse societies (Chohan 2021).
Beyond the hype of multi-million dollar digital art sales (Pawelzik and Thies 2022), the significance of NFTs may lie in enabling the beginning of something resembling genuine human society in the metaverse, a society based on free markets (for goods, services and ideas), independent ownership and social contracts.
Therefore, what about the cultural heritage? Is the culture ready for this?
For example, in Italy the General Directorate of Museums of the MiC – Ministry of Culture has asked its museum and archaeological sites to suspend contracts with technological companies regarding the digital reproduction of the works of their collections. The decision was taken following the controversy that arose around the “Tondo Doni”, Michelangelo’s masterpiece preserved by the Uffizi Galleries, whose digitised version, certified via NFT on blockchain by the Cinello company, was sold for 240 thousand euros, of which 70 thousand went to the important museum institution (Artnet News 2021).
Beyond bombastic news in the newspaper front pages, discourses around the potential of hard digitisation of cultural assets, for example in museums, as well as the minting of real art pieces into NFTs are steadily growing also in the scientific literature (Valeonti et al. 2021); moreover, even though the ‘virtual’ discourse is now quite old (Pujol Tost 2008), cultural heritage project are starting exploring virtual reality and metaverse’s strengths and weaknesses (Hugget 2020) in a coherent way, reasoning on the anthropological and societal value of ‘immersivity’ as a fundamental bridge between the past and the contemporary people that own it. Finally, studies on metaverse as part of conservation methodologies have been recently explored (Gaffar 2021).
What will be the next experiences in Blockchain, NFTs and metaverse is difficult to say. Multi-scenarios are yet to be explored and the development in this field increases exponentially every day, even when cultural heritage is addressed.
The session invites the submissions of original papers in the area highlighted above (i.e. metaverse, immersivity, blockchain, NFTs, virtual online spaces) and beyond, both through the presentation of past and on-going projects or with critical and methodological perspectives, in order to highlight established and emerging methodologies as well as the positive or negative implications of the growing entrance of Cultural Heritage in the virtual world.
Pawelzik, L, and Thies, F 2022. Selling digital art for millions – a qualitative analysis of NFT art marketplaces. ECIS 2022 Research Papers. 53. https://aisel.aisnet.org/ecis2022_rp/53 [last accessed: 2022-08-29]
Chohan, U W 2021. Non-Fungible Tokens: Blockchains, Scarcity, and Value. Critical Blockchain Research Initiative (CBRI) Working Papers. DOI: http://dx.doi.org/10.2139/ssrn.3822743
Valeonti, F, Bikakis, A, Terras, M, Speed, C, Hudson-Smith, A, Chalkias, K 2021. Crypto Collectibles, Museum Funding and OpenGLAM: Challenges, Opportunities and the Potential of Non-Fungible Tokens (NFTs). Applied Sciences.11(21):9931. DOI: https://doi.org/10.3390/app11219931
Artnet News 2021. The Uffizi Gallery Just Sold a Michelangelo NFT for $170,000, and Now Is Quickly Minting More Masterpieces from Its Collection.https://news.artnet.com/art-world/uffizi-gallery-michelangelo-botticelli-nfts-1969045 [last accessed: 2022-08-29]
Huggett, J 2020. Virtually Real or Really Virtual: Towards a Heritage Metaverse. Studies in Digital Heritage, 4(1), 1–15. DOI: https://doi.org/10.14434/sdh.v4i1.26218
Pujol Tost, L 2008. Does Virtual Archaeology Exist? In: Axel Posluschny, Karsten Lambers and Imela Herzog eds. Layers of Perception. Proceedings of the 35th International Conference on Computer Applications and Quantitative Methods in Archaeology (CAA), Berlin, Germany, April 2–6,
Gaffar, A A M, 2021. Metaverse in Heritage Conservation Evaluation “Using Fully Immersive Virtual Reality Techniques to Evaluate Preservation Quality”. International Journal of Architecture, Arts and Applications. 7(4): pp. 97-106. DOI: 10.11648/j.ijaaa.20210704.11
S41. Capacity building for open data persistence in archaeology
Holly Wright, University of York
Edeltraud Aspöck, Austrian Academy of Sciences, Austria
Session type: Standard
As we work to increase the amount of archaeological data that is freely available online, much of the data that is currently available still cannot be considered to be persistent. In other words, just because something is online, doesn’t mean work has been undertaken to ensure it will be available in five or ten years time (and beyond). Even with the best of intentions, data that has been archived for the long term remains the exception, rather than the rule. This has resulted in a myth of persistence; the incorrect assumption that once something is made openly available online, it will continue to be available. An understanding of, and commitment to, the stewardship of our digital archaeological resources for the long-term is still very much lacking.
The European Commission places international collaboration as a central tenet within most of its funding initiatives, and collaboration is the cornerstone of successful digital archaeological data stewardship. Funded by the European Commission’s Horizon 2020 research and innovation programme under Grant Agreement 823914, and implemented in parallel with SEADDA, ARIADNEplus consisted of 41 partners representing 23 countries and four international partners, working together to build a data aggregation infrastructure to serve the archaeological community worldwide, through the ARIADNE Portal (https://portal.ariadne-infrastructure.eu/). Data-providing partners in ARIADNEplus encountered challenges in how best to map and organise their metadata in order for it to be incorporated and made discoverable within the ARIADNE Portal, but some partners encountered greater barriers than others. Barriers include lack of technical capacity in preparing their data; lack of background in data stewardship; and lack of an appropriate, persistent repository to house their data. The current development phase of the ARIADNE Portal has recently come to a close, but collaborative work continues and preparations are already underway for the next phase. This will include finding new data providing partners, expanding current collaborations, and enhancing data reuse, but with the added understanding derived from SEADDA around the importance of capacity building for data persistence which has also been an entry point for early career researchers and researchers working outside of academia.
This session invites papers from ARIADNEplus partners and SEADDA members to share their progress in capacity building in their country and/or region, as we seek to raise the visibility of data persistence within the CAA community. This session equally invites submissions from outside SEADDA and ARIADNEplus that discuss issues around data persistence, preservation, stewardship and capacity building in this area, including practical challenges, opportunities, along with ethical and theoretical considerations, such as where individual researchers, who are always pushed to prioritise innovation over preservation in their work, stand in this debate.
Geser, Guntram, Salzburg Research Institute, Julian D. Richards, Flavia Massara, Holly Wright, Archaeology Data Service, Central Institute for the Union Catalogue of Italian Libraries, and Archaeology Data Service. 2022. “Data Management Policies and Practices of Digital Archaeological Repositories.” Internet Archaeology, no. 59 (March). https://doi.org/10.11141/ia.59.2.
Richards, Julian D., Ulf Jakobsson, David Novák, Benjamin Štular, and Holly Wright, eds. 2021. “Digital Archiving in Archaeology: The State of the Art” 58 (June). https://doi.org/10.11141/ia.58.23.
S42. Citizen science in archaeology. Possibilities and challenges
Steinar Kristensen, Museum of Cultural History, University of Oslo
Session type: Standard
The public has through the times of museums contributed to and enriched the museum’s collections. By voluntary effort from submission of finds to preservation and sharing of local knowledge and traditions the public have helped and cooperated with the scientists.
The term ‘citizen science’ draws attention to various aspects of such joint knowledge building – including the roles and relationships between different participants. Sometimes researchers get help to collect, analyse and disseminate data. At other times, interested parties can identify and explore different questions by themselves or together with researchers. Our digital world provides today new and interesting opportunities for engagement between the public and science.
In biology citizen science projects have for years contributed to increase the numbers of observation of bird and marine animals. For archives written documents are transcribed and in archaeology one of the largest contributions later year – metal detecting – has “all” been done by the help of the citizens. At its best, the engagement with the public through citizen science can highlights opportunities that exist for open, dialogical, and democratic conversations and collaborations across society – with museums as active participants. There is great potential for further collaboration, knowledge development and sharing.
Citizen science can open the knowledge jar of Sarepta for archaeology and bring new and groundbreaking knowledge to our field. There are aspects of this that must be reflected on before a citizen sciences project is started and this session will seek to enlighten some of these aspects.
We must honestly ask ourselves what do museums intend with citizen science, and what do citizen scientists expect from museums? How can technological solutions facilitate collaboration and involve the public in a good and rewarding way and who is invited inside, and who is left outside?
You are invited to contribute with your experiences and thoughts on this topic ranging from the choice of digital solutions and resources to the strategic thinking, involvement, and ethical perspective.
Dobat, Andres S. (2013) Between Rescue and Research: An Evaluation after 30 Years of Liberal Metal Detecting in Archaeological Research and Heritage Practice in Denmark, European Journal of Archaeology, 16:4, 704-725
Gibb, James G. (2019) Citizen science: Case studies of public involvement in archaeology at the Smithsonian Environmental Research Center, Journal of Community Archaeology & Heritage, 6:1, 3-20,
Smith, Monica. (2014). Citizen Science in Archaeology. American Antiquity. 79. 749-762. 10.7183/0002-73220.127.116.119749.
S43. Synergies in 3D Spatial Analysis
Gary Nobles, Oxford Archaeology
Alexander Jansen, Durham University
James Taylor, University of York
Markos Katsianis, University of Patras
Session type: Standard & Lightning talks
The purpose of this session is to bring together researchers who are combining the diverse archaeological fields with 3D spatial analysis. This will mark the 3rd and final explorative session into the application of 3D Spatial Analysis across the archaeological discipline facilitated through the CAA’s Special Interest Group in 3D Spatial Analysis. While not essential, we would appreciate speakers to consider how their thematic area of expertise (e.g. lithics, ceramics, A-DNA, botany, zoology, chemical (phosphate) etc.) or other analytical area combine in 3D space and how the benefits of analysis in 3D space can help to develop the greater narrative. We continue to ask the fundamental questions: – 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 from those who are working in three dimensions from across the diverse spectrum of applications. We particularly welcome papers which bring together different aspects of archaeological analysis within 3D space. Papers should go beyond presenting methodologies involving the capture of data, by instead discussing the analysis of 3D (or 4D) datasets. Any form of 3D spatial data is welcome, papers may push the boundaries (theoretically or technologically) or be presented as position papers. Amongst others, past topics have included:
– 3D Landscape Archaeology
– 3D Excavation and Post-excavation Analysis
– 3D Material Studies (e.g. lithics, ceramics)
– Geochemical Analysis in 3D space
– Investigating Visibility/Gaze/Gesture/Mobility and Perception in 3D space
– Machine Learning/AI in 3D Space
– 3D Networks and Semantic Modelling
– 3D Analysis in Virtual Reality
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, 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 session’s principal themes which emerge from the presented papers, and incorporating elements from the discussions of previous years. Facilitated through the 3D Spatial Analysis CAA SIG, we endeavour to keep these discussions continuing beyond the meetings at CAA International.
S44. Roads to Complexity: Technological and Quantitative Approaches to Human and Objects Connectivity
Sandro Parrinello, Università degli Studi di Pavia
Lorenzo Zamboni, Università degli Studi di Milano
Daniele Bursich, Università degli Studi di Salerno
Session type: Standard
Connectivity is how people and things relate with each other through space and time, and
roads are a primal and widespread human strategy to achieve this crucial goal in evolutionary
and historical terms.
A road is a hinge between individuals and cultures, along the road events happen, stories
intertwine, goods are exchanged and cultural processes spread leading to the nourishing of
communities and territories. Both as trails or engineering works, roads usually depart from
given ‘centers’ to reach remote territories, creating new paths for interaction and cultural
The analysis of connectivity and its material signs is a common research topic in the current
archaeological agenda, with several case studies showing the degree of human-things
entanglement. However, understanding past movements requires a shift from traditional
archaeological ontologies, grounded in fieldwork and descriptive studies, towards more
Moreover, the landscape along a road is constantly changing, in synergy (or in contrast) with
other natural and human features and leading to endless potential variations over time. There
are therefore many types of roads embedded in urban, rural or even deserted landscapes,
connecting territories through several modes and tempos of mobility.
The street is the privileged place for the movement of human society that moves through the
cities. But also from city to city, from settlement to settlement. Within the public and private
spaces intended for movement and mobility, human relationships flourish. These are the
places where knowledge is born: here are new practices such as barter which then turns into
commerce, the traffic and movement of goods, as well as the spread of art, which is
contaminated through social relations (Greek potters for example).
There are also peoples based on movement, such as the caravan cities, which trade goods
from the Far East, becoming the privileged places for markets and street vendors who move
from one continent to another. As well as trade motivated by religion, which is a very strong
reason for cultural influence, both in settled populations and in nomadic ones by vocation.
The road / path / trail is also the privileged place for the pilgrim who moves from one
religious place to another.
The streets have also constituted international commercial networks since the Bronze Age,
the privileged dimension for the breeding of cattle through mountain paths, the
standardization and the new invention of Roman roads, which constitute one of the success
factors of the Roman empire, up to intangible paths such as the aboriginal “ways of songs”.
This session welcomes papers dealing with human connectivity and objects mobility through
the application of new technologies and state-of-the-art methods. Any type of connectivity
and any category of infrastructures could be explored, including: physical and immaterial
pathways, road construction techniques and maintenance, the archaeology of roads and
streets in urban and landscape context. More specifically, we want to explore how road architecture could have influenced common and transit spaces, which agency do roads have
in cultural and socio-economic terms.
These investigations are increasingly characterised by digital technologies (network analysis,
big data, surveys, space syntax, and so on), which allows us to promote reconstructions,
hypotheses and simulations, adding greater descriptiveness and coherence to the research
We also encourage the submission of papers dealing with geospatial and statistical analysis,
network analysis, and of course reconstruction of sections of routes with innovative and
Acquiring, viewing and disseminating data through dynamic databases therefore produces a
shift from traditional methods of recording information, promoting new ways of using