In conflict archaeology, KOCOA—an acronym for Key terrain, Observation and fields of fire, Concealment and cover, Obstacles and Avenues of approach—is a widely used methodology for battlefield terrain analysis. Its field of fire and cover aspects are usually identified by visibility analysis and the superimposition of shooting ranges is derived from firing tables to define a simple perimeter. In reality, shooting range varies, especially in terrain with high elevation differences. Additionally, projectiles may still impact areas rendered invisible by complex terrain or anthropogenic obstructions. Therefore, we here present a ‘throwshed’ analysis approach, which delineates the areas reachable by projectiles shot from any given place while respecting the complex terrain or surface in the form of a digital elevation model and applying the physical laws of external ballistics. The main aim of this paper is to demonstrate the classical shooting range approach within KOCOA and to resolve it by throwshed analysis. Moreover, this work aims to present the functionalities of the developed tool in diverse use cases by modifying the settings to demonstrate the innovative potential of the analysis within the KOCOA methodology. The physical model is validated with current, historical, and archaeological data. The validation and demonstration of the throwshed tool indicate that it corrects significant issues in the classical handling of fields of fire and cover within the KOCOA analysis. The throwshed tool is an open-source Python package that is freely available on GitHub.
The Baths of Syracuse (3rd century BC), located in the ancient city of Syracuse (modern Siracusa) in Sicily, Italy, are an important representative of Hellenistic public bath architecture. This study examines the spatial configuration of the Baths of Syracuse to identify architectural type and spatial hierarchy. Comparative spatial analyses with other Hellenistic baths in Sicily and a Roman imperial bath situate the Syracuse baths within a broader archaeological research context. This study integrates architectural design theory with space syntax methods and the Depthmap software (Turner 2001) to analyze the archaeological remains of the Syracuse baths, offering a quantitative and visual approach to understanding their spatial organization. By converting the bath spaces into Justified Plan Graphs (JPGs), this study applies three data models — connectivity, Integration, and Visibility Graph Analysis (VGA) — to examine the complex’s spatial configuration. This approach combines visual representation with quantitative analysis to evaluate the bath complex’s spatial organization. Comparison of the case study demonstrates the value of space syntax as a quantitative tool for spatial analysis. The results contribute to discussions on the development of Mediterranean public bathing architecture from Greece to Rome.
Hominins lived for most of their history as foragers in complete dependence on plants and animals in their surroundings. Depending on the regions they occupied, the available resources may have differed greatly intra- and inter-annually while shifts in climate altered the available ecosystems over time. How hominins may have behaved under these conditions and adapted to new challenges is increasingly studied using agent-based models (ABMs), as they allow researchers to recreate different behavioural and environmental scenarios and test the consequences (i.e., home range size, viability of the group). The goal of this article is to provide a comprehensive overview of the current state of research on ABMs simulating hominin foraging behaviour and connected processes, highlighting key findings, methodologies and theoretical frameworks. Our analysis reveals several prominent trends in the application of ABMs focused on hominin foraging behaviour, including the use of optimal-foraging (OFT) or central-place foraging (CPF) approaches. Additionally, we identify common challenges faced by researchers, such as implementing suitable reactions of the hominins to varying environmental conditions without relying on CPF, the difficulties in implementing comprehensive interactions between foragers and how to observe and interpret the resulting behaviour. This paper underscores the importance of refining ABMs to better capture the complexity of subsistence strategies in foraging hominins. We propose future directions for research that could enhance model accuracy and applicability.
Museums frequently display artefacts removed from the landscapes where they were found and used, weakening visitors’ ability to understand object–place relationships. This article investigates whether mobile augmented reality (AR) can help re-establish such relationships by re-placing museum objects within their archaeological contexts. At the Lofotr Viking Museum (Borg, Lofoten, Norway), a prototype mobile AR application was developed that anchors full-scale reconstructions to the original settlement footprint and embeds selected museum artefacts as interactive 3D objects within these reconstructed environments. The prototype was refined through an iterative design cycle and evaluated in two in-situ test rounds (N = 31; January 2025 and September 2025) using short post-use surveys and go-along observation. The evaluation focuses on (1) usability and interaction clarity, and (2) object–place comprehension in a hybrid setting where physical reconstructions, archaeological absence, and digital overlays coexist. The results show that mobile AR can enhance visitors’ understanding of artefacts’ original spatial relations, but that spatial placement alone is not enough. Understanding improved when explicit narrative cues, especially audio prompts, clearly connected digital objects to their counterparts in the indoor exhibition. At the same time, minor tracking drift and ambiguous visual similarity between physical and digital structures produced disproportionate confusion in areas where reconstructions and overlays competed for attention. It is argued that successful heritage AR in hybrid museum landscapes depends less on the novelty of digital reconstructions than on careful coordination of narrative guidance, visual differentiation, and spatial anchoring. The study contributes empirical evidence on where object–place understanding breaks down in real-world use and proposes design strategies for reducing interpretive ambiguity.
This paper examines the potential of using game engines and virtual reality devices to study the 2nd century BC Koan Asklepieion during festivals. Building on earlier visualisations and functional hypotheses, the study explores how digital environments enriched with moving human and animal bodies can facilitate a praxeological analysis of the built space. It discusses the feasibility of processional routes via gates and staircases, and the suitability of different areas within the Asklepieion for sacrifice, gathering, and observation by humans and animals. It also explores how physical features, such as steep slopes and looming retaining walls, shaped the spatial experience, making them important for festival logistics too. By relating movement and perception rooted in the body to the material record, the study demonstrates that game engines can be employed to bridge the void left by the ephemeral presence of past participants. Ultimately, the paper discusses ways of using digital tools to study the social production of past built space.
This study presents a proof-of-concept for integrating 14 datasets on 11 archaeologically relevant raw materials from the Big Exchange project into a heterogeneous information network (HIN), an informational structure explicitly modelling multiple object and relationship types. HIN-based approaches provide archaeologists with a powerful means of identifying structural and semantic patterns in material distributions. In this study, a spatial extension of the PathSim similarity measure is applied to the integrated HIN to quantify higher-order relationships (meta paths) between raw materials at different spatial scales. The results highlight overlapping material spheres as proxies for potential contact zones and social proximity in the Early Neolithic. They also reveal instances of spatial separation and limited interaction. The method additionally helps distinguish circulation patterns from potential taphonomic biases, such as artefact absence due to preservation conditions. The analysis reveals a particularly strong similarity between Rijckholt Flint and Actinolite-Hornblende Schist at all spatial scales. This suggests that there was sustained contact and low social distance between the communities associated with them. These findings show how spatially extended PathSim can reveal both expected and previously obscured interaction patterns, while also highlighting methodological limitations that result in localised variations in similarity scores being flattened by highly dispersed materials.
In a world of drastic climatic and ecological changes, our knowledge of how the environment influenced hominin behaviour is of the utmost importance. Archaeology plays a key role in this domain, as it is the only discipline that studies empirical evidence of past societies’ responses to environmental change. Computational models generating predictions about past climatic and ecological conditions are vital for understanding the archaeological record and how these factors shaped the dispersal of hominins out of Africa and into Eurasia during the Early and early Middle Pleistocene. In this paper, various models for past reconstructions of climatic and ecological conditions and simulation techniques are presented to provide an overview of the diverse approaches, possibilities, advantages and constraints of using computational reconstructions in archaeological research. Focusing on studies of hominin dispersals out of Africa and into Eurasia during the Early and early Middle Pleistocene, this paper discusses the links between environmental factors and hominin dispersal behaviour. The use of simulation techniques to represent hominin populations, such as cellular automata or agent-based modelling, can contribute to connecting small-scale environment-induced influences on hominins to large-scale patterns, supported by ecological theories of species survival and spatial behaviour. Collectively, these approaches provide an elaborate foundation for understanding environmental influences on past hominin dispersals.
About 1,000 years ago, Central Cahokia, located in modern day Illinois on the floodplain opposite St. Louis, Missouri, was a thriving city with thousands of residents. The region around Central Cahokia, filled with farmers and laborers, is called Greater Cahokia. Ongoing excavations at Greater Cahokia have revealed a larger and more complex landscape than previously understood, even though much of the site has been lost to development throughout the years. Using clustering and intervisibility analysis, this research studied the regional spatial design of residential, mound, and elite sites at Greater Cahokia. First-order spatial properties are assessed using average nearest neighbor and kernel density estimates. LiDAR data of the region was used to create a bare earth terrain raster for line-of-sight analyses to compare archaeological sites to random points across the landscape, which afforded an empirical analysis of Greater Cahokia’s land use. Results indicate that the location of mounds and residences at Greater Cahokia exhibited statistically significant clustering. Additionally, being visible may have been an important consideration for the population of Greater Cahokia, with most occupied habitation sites and individual mounds constructed within view of a main mound group. Further, these archaeological sites were more visible than random points within the same extents. These results are suggestive of shared and coordinated decision making for construction projects at Greater Cahokia. Additionally, the findings identify areas to concentrate future conservation and excavation efforts due to the concentration of archaeological features connected with preferences for location visibility.
In recent years, the increasing application of machine learning (ML) techniques to solve archaeological problems has garnered substantial interest. The relevant issue is that limited-sample, heterogeneous, and non-standard structures of datasets in archaeology affect the quality of deep learning (DL) model efficiency in training and testing. This study explores the effectiveness of artificial neural networks (ANNs) in addressing the unique challenges posed by the classification of Hittite stelae fragments, given a reduced set of well-known samples for training and testing. A hybrid model combining Model-Agnostic Meta-Learning (MAML) and Few-Shot Learning (FSL) is compared to a transfer learning approach (ResNet18 architecture), as well as conventional classificatory methods. This hybrid approach has been successful in other research domains for training ML and DL models with small datasets. This paper critically evaluates these approaches, addressing key challenges based on small training and testing datasets, the effects of fragmented and altered archaeological data in automated learning, and variable documentation quality, thereby underscoring the advantages of the proposed method over conventional ML and statistical techniques. Additionally, insights from a Hittite art expert were incorporated to assess the practical benefits of our models in this study on the same classification task. Our preliminary results on the provenance of stelae from four different Hittite cities indicate that effective classification and origin prediction are achievable with only 208 samples enabling systematic analysis of how different algorithms and human expertise respond to increased data state. Gradient-weighted Class Activation Mapping (GRAD-CAM) analysis confirmed the performance of models in base classification decisions on archaeologically meaningful iconographic features rather than photographic artifacts, validating their authenticity for scholarly applications. The code for programs used in the paper can be accessed on https://github.com/dkayikci/ML-Arch.
This article details a correction to: Visser, R.M., Lambers, K., Aitchison, K., Jutte, A., Rocks-Macqueen, D., van der Knaap, L., Romanowska, I., Brughmans, T., Linssen, J. and Pažout, A. (2025) ‘Lessons Learned: Creating Tutorials to Teach Agent-Based Modelling to Archaeologists’, Journal of Computer Applications in Archaeology, 8(1), p. 354–367. Available at: https://doi.org/10.5334/jcaa.241.
This research addresses the imperfection in archaeological data — ambiguity, partiality, imprecision, and uncertainty — through a fuzzy logic-based framework to measure uncertainty in site chronologies and typologies. The framework integrates expert interpretation and applies fuzzy operators to quantify uncertainty, particularly in dating and typology, using trapezoidal functions for fuzzification. By introducing metrics like CDEG (Comprehensive Degree of Equivalence) and FEQ (Factor of Equivalence), the framework provides a replicable approach to assessing and managing uncertainty in legacy data. Case studies from San Blas and Santa María de Hito demonstrate the model’s adequacy in quantifying uncertainty at various stages of investigation, offering a more flexible classification and analysis of incomplete or uncertain archaeological data. This approach enhances the reliability of archaeological research and improves the management of data by providing clear, measurable metrics for uncertainty in both chronology and typology.
Natural disasters and intensive land use increasingly threaten archaeological and cultural heritage (ACH) sites. To address this, the German Archaeological Institute (DAI), with the Leibniz Centre for Archaeology (LEIZA) and the Federal Agency for Technical Relief (THW), launched in 2021 the project KulturGutRetter (KGR), establishing a rapid-deployment Cultural Heritage Response Unit (CHRU) with the focus on safeguarding worldwide cultural heritage at risk after disasters. While the CHRU has not officially declared operational readiness yet, it was able to gain valuable experience during a national full-scale exercise and by participating in an EU MODEX (Module Exercise) in the Venice Lagoon (both in autumn 2024; e.g. Papa et al., 2025), which it has incorporated into its further development. Part of this experience also relates to the digital infrastructure, which CHRU relies on for efficient and uniform data collection during operations. Before, during and after missions, the CHRU employs fully open-source, standardised workflows for the documentation and assessment of affected cultural heritage, spanning the entire disaster-response chain. Before teams are dispatched, a remote-sensing and GIS (Geographic Information Systems) support group compiles the latest satellite imagery, augments it with the in-house “KGR Finder” archaeological tool, and produces layered risk and damage maps. These datasets, packed together with a standard data model, are loaded to handheld devices running mobile GIS software for immediate field use. On site, CHRU team members record damage through structured digital forms and, when conditions allow, they conduct UAV (Unmanned Aerial Vehicle) photogrammetry, laser scanning and other 3D survey methods. Moveable artefacts are registered on the spot: each object receives a QR-coded ID-card, enabling real-time assessment and tracking. A portable IT stack underpins this workflow. A mobile server hosts a PostgreSQL/PostGIS database, network-attached storage and synchronisation services, all accessible via an ad-hoc Wi-Fi or local cellular network. This lets teams consolidate data from multiple instruments instantly, secure it redundantly and keep every device in sync even in disconnected environments. After a mission, all remotely sensed and field data that are free of third-party restrictions are transferred to the host nation’s antiquities authorities as a structured package, then archived on DAI servers for future research and publication upon agreement. The field records also provide essential ground truth for refining satellite-based assessments. This paper outlines the open-source technologies, data standards and practical lessons that make CHRU deployments globally scalable, rapid and resilient, thus offering a blueprint for safeguarding ACH under growing disaster pressure. Highlights • A general overview of all the digital components of the CHRU is given • We illustrate the workflow of different components and how the data is gathered or recorded and further analysed • Data management infrastructure is described, including both software and hardware perspectives • The aim is to make a clear workflow of handling different datasets from the beginning to the end of a mission
This paper presents a systematic literature review on advancements and applications of Finite Element Methods (FEM) and Laser Scanning Documentation (LSD) in Cultural Heritage Management. FEM is a numerical technique widely used in engineering and scientific disciplines for solving complex problems by dividing them into smaller, more manageable elements. LSD is a method for capturing and digitizing real-world objects and environments using laser scanning technology. The objective of this review is to explore recent advancements and diverse applications of FEM and LSD, as well as their combined utilization for enhanced analysis and documentation, and identify research gaps. Literature search was conducted systematically, covering research articles in the Scopus, Web of Science and ScienceDirect databases. The review further investigates the integration of LSD with FEM, focusing on the use of laser scanning technologies for accurate geometry acquisition, mesh generation, and model validation in the field of Cultural Heritage. A total of 60 articles were identified, on which data analysis was performed using thematic analysis. As a result, seven thematic areas were identified: Structural Assessment, Cloud2FEM Methods, Modeling, Deformation, Techniques, Diagnostics and Digital Twins (DTs). The findings of this review demonstrate a limited range of applications where FEM and LSD have been successfully employed. The review identifies emerging trends and future directions in the field and techniques to optimize FEM simulations and enhance LSD data processing. It provides a comprehensive overview of advancements and applications of FEM and LSD and identifies the need for further research, especially in integration of FEM and LSD in cultural heritage documentation.
The dairy industry has played a central role in the economy of the Alps for many centuries, and archaeological evidence suggests a prehistoric origin for this practice. During the Bronze Age, the Alps experienced a rapid increase in upland pastoralism, attributed to the growing importance of cheese production for the subsistence of human communities in the region. However, the effects of dairy specialisation on prehistoric mountain economies remain unexplored. Furthermore, the impact of dairy-focused pastoralism on the vulnerable ecosystems of the Alps has largely been speculative so far. A mathematical model was developed to formally investigate how the intensive exploitation of milk affects labour efficiency and land use in prehistoric subsistence systems. Model parametrisation was based on archaeological information available for the Alps, as well as ethnographic analogues. Sensitivity tests were conducted to assess the reliability of the parameters and the robustness of the model. Four scenarios were created by adjusting the contributions of crop and animal farming, as well as the importance of cheese making in the model. The results clearly show that a crop-farming economy supplemented by intensive dairy production provides the best labour return using the least amount of land. The same economic strategy without milk exploitation appears to be the least efficient in terms of labour and land use. A system primarily focused on pastoralism also seems unsustainable. These tests suggest that dairy specialisation was crucial for the development of Bronze Age societies in the Alps. It transformed dairy products into important commodities, contributing to the Stored-Product Revolution across the continent. The higher labour return could have also fostered demographic growth in the region.
Agent-based modelling (ABM) is one of the most widely applied computational modelling research techniques in archaeology, because it is well suited to the questions asked by archaeologists. However, the access to vocational training for ABM is limited. In this paper we present the Open Educational Resources (OER) that we produced in an international cooperation. For this purpose, we created online and open tutorials for ABM for archaeologists. In addition, how-to guides and support material were created, both for teachers and students. The materials adhere to international (European) standards in relation to education and the Digital Skills Passport for archaeology. The teaching materials have been well tested using a diverse group of archaeologists during various international conferences and meetings. It was shown that the knowledge and skills of the participants in relation to ABM improved. In addition, the demand for the teaching materials and the workshops was high, ensuring that the tutorials on ABM will be used in the future.
Heritage data management has become increasingly critical as regeneration initiatives generate vast quantities of digital information, yet systematic approaches to data governance remain inconsistent across the sector. This paper examines heritage data practices within England’s High Street Heritage Action Zone (High Street HAZ) programme, focusing on case studies from Northallerton, Kirkham, and Chester. Through semi-structured interviews, questionnaires, and data audits conducted between 2021–2024, this research investigates how heritage datasets are created, shared, and preserved within planning processes, community wellbeing initiatives, and heritage research projects. Key findings reveal widespread data reuse across all programme strands, alarmingly low awareness of Data Management Plans (DMPs), and fragmented approaches to data sharing and preservation. The study uncovers significant disparities between above-ground and below-ground archaeological data management, with the former lacking systematic archival requirements despite comparable heritage value. Commercial intellectual property practices often conflict with public access principles, whilst community-generated datasets face particular vulnerability without institutional support. The research demonstrates that easily accessible datasets are routinely reused whilst those requiring specialist access remain underutilised, highlighting the critical importance of data discoverability. The paper advocates for mandatory DMPs, hybrid governance models balancing local autonomy with national oversight, and clear intellectual property frameworks ensuring public benefit from publicly funded research. These findings contribute to emerging debates on digital heritage governance, offering evidence-based recommendations for improving data stewardship in heritage-led regeneration initiatives.
This paper presents a multi-modal method for integrating rock-cut structures into current archaeological studies related to Ancient and Medieval periods, particularly focusing on a case study of the north-west wall of the Göreme 4b church in Cappadocia (Turkey). Historically marginalised within archaeological research, rock-cut architecture is now reassessed through a combination of building archaeology, traceology, photogrammetry, and computer-assisted analysis. The primary objective is to establish a replicable protocol for interpreting tool marks to define construction phases and occupation sequences, thereby contributing to relative dating and heritage conservation. The interdisciplinary project involved the creation of a high-resolution 3D model, a relational database, and a GIS-based vectorisation of stratigraphic units (SUs). The 3D models—generated from DSLR and smartphone photogrammetry—facilitated the production of orthophotographs and digital elevation models, essential for precise tool mark analysis. Using controlled vocabularies and standardised descriptors, the relational database supports both qualitative and quantitative analysis, enabling cross-referencing across architectural features and excavation contexts. GIS software was employed to integrate geospatial data, allowing for the vectorisation and chronological ordering of identified SUs. The results demonstrate the utility of this method in clarifying previously unseen features, such as a Christian cross near a tomb and stratigraphic relationships between excavation phases. Notably, the method confirmed that initial excavation proceeded from the top down, and identified multiple phases of tool use, including quarry picks and polkas. Although more time-consuming than traditional CAD-based methods, the systematic protocol enhanced interpretive precision. This approach offers significant advantages for understanding site chronology and spatial dynamics, and can be extended to larger areas and other structures. Future developments may incorporate artificial intelligence for automated tool mark recognition. The study underscores the potential of integrating digital technologies into archaeological research to refine structural analysis and conservation strategies.
XRONOS (https://xronos.ch) is an open data infrastructure for the backbone of the archaeological record – chronology. It provides open access to published radiocarbon dates and other chronometric data from any period, anywhere in the world. By collating a large number of existing regional and global compilations of dates, XRONOS offers the most comprehensive radiocarbon database yet published, with over 350,000 radiocarbon and 75,000 site records. It also provides a foundation for expanding the systematic collection of chronometric information beyond radiocarbon, with support for typological and dendrochronological dates and a generalisable data model that can be adapted to other methods of absolute dating. Automated and semi-automated quality control processes ensure that data from diverse sources is continuously integrated and standardised, making it easier to find information of interest and reducing the need for manual data cleaning by end users. In this paper we describe the concept and implementation of XRONOS in relation to the state of the art in chronometric data-sharing and evaluate its potential as a general-purpose open repository and curation platform for archaeological chronology.
The conservation of archaeological heritage is important for understanding and preserving human history, but conventional approaches often cannot deal effectively with the magnitude and complexity of modern issues. The integration of AI (artificial intelligence) into archaeological methodologies is enhancing research, analysis, and preservation practices. This paper focuses on the changing dynamics of AI applications in archaeological research, pointing out the phases of trend detection, technological progress, and collaborative networks: using bibliometric analysis, co-authorship networks, and keyword density visualizations, we select the dominant topics affecting the discipline, such as ML (machine learning), remote sensing, and predictive modelling. The data indicates that new technologies, such as automated detection systems and neural networks, have greatly improved strategies for site discovery and preservation. However, there exist significant issues like data access, ethical concerns, and technology inequalities across research fields. This study aims to provide a thorough and up-to-date synthesis of AI’s role in archaeology, highlighting its potential to define new best practices for heritage conservation and defining a framework for future research and collaboration. Finally, this research underlines the importance of using interdisciplinary approaches to ensure that AI serves not only as an efficient tool, but also as an ethical and sustainable means of maintaining humanity’s shared cultural heritage.
This paper examines the current status of 3D modelling of cultural heritage objects in Australian universities, focusing on how these models are being integrated into object-based learning practices. It discusses the different approaches taken by major universities, explores the motivations behind digitisation projects, and considers the benefits and challenges they present. The paper provides an overview of various digitisation techniques and the separate metadata recording practices that have been developed. It argues for the use of digital surrogates in object-based learning and research while also identifying key challenges that are limiting the potential of cultural heritage 3D modelling. These include the ad hoc nature of digitisation projects, inconsistent funding, and a lack of standardisation in data management and metadata practices. The paper emphasises the importance of long-term planning and collaboration both within and between universities to develop skills, standards, and shared resources.
