Iris Breda, Glenn van de Ven, Sabine Thater
et al.
A central topic in extragalactic astronomy is understanding the formation and evolutionary histories of galaxies. These systems often comprise multiple structural components with distinct physical and dynamical properties, making it challenging to disentangle their individual contributions. Aiming at investigating the true structure of the inner stellar disk, we have developed a comprehensive pipeline for the chronochemical and dynamical analysis of galaxies (Glance: Galactic archaeoLogy via chronochemicAl & dyNamiCal modElling). The presented pipeline employs several state-of-the-art techniques by integrating them into a single, automated pipeline, enabling streamlined analysis of integral-field spectroscopy data, by allowing users to easily and directly extract valuable information on stellar populations, kinematics, dynamics, and gas properties. It automates multiple analysis techniques, including stellar population synthesis (Fado, Starlight, post-processing with RemoveYoung, kinematic extraction (pPXF, Bayes-LOSVD), and dynamical modelling (Dynamite). It handles tasks such as Galactic extinction correction, de-redshifting, Voronoi binning, and nebular continuum correction, while offering extensive customization options. Parallel processing significantly reduces computational time. When applied to MUSE data sampling the central region of NGC 1566, this methodology reveals that its stellar disk significantly deviates from the conventional exponential model, challenging the assumption of universality in disk morphology. In summary, this work presents a powerful, publicly available pipeline for conducting galactic archaeology, designed to advance our understanding of the formation and evolution of galaxies.
This technical note presents a reproducible workflow for converting a legacy archaeological image collection into a structured and segmentation ready dataset. The case study focuses on the Lower Palaeolithic hand axe and biface collection curated by the Archaeology Data Service (ADS), a dataset that provides thousands of standardised photographs but no mechanism for bulk download or automated processing. To address this, two open source tools were developed: a web scraping script that retrieves all record pages, extracts associated metadata, and downloads the available images while respecting ADS Terms of Use and ethical scraping guidelines; and an image processing pipeline that renames files using UUIDs, generates binary masks and bounding boxes through classical computer vision, and stores all derived information in a COCO compatible Json file enriched with archaeological metadata. The original images are not redistributed, and only derived products such as masks, outlines, and annotations are shared. Together, these components provide a lightweight and reusable approach for transforming web based archaeological image collections into machine learning friendly formats, facilitating downstream analysis and contributing to more reproducible research practices in digital archaeology.
Predictive modeling in archaeology is essential for the understanding of people's behavior in the past and for guiding heritage conservation. However, spatial sampling bias caused by uneven research effort can severely limit model reliability. This research describes a novel new framework that integrates entropy-based corrections to measure and minimize such biases in archaeological modeling of foresight. Leveraging the open access data of the Grand Staircase-Escalante National Monument, we employ Shannon entropy to determine survey coverage and assign appropriate weights to pseudo-absence points. We combine these weights with predictive models such as Bayesian Spatial Logistic Regression (via R-INLA), Generalized Additive Models, Maximum Entropy and Random Forests. Our findings prove that entropy-aware models exhibit improved accuracy and robustness, especially for under-surveyed regions. This approach not only advances methodological transparency, but also improves the interpretation of archaeological prediction under conditions of data uncertainty. The proposed framework offers a scalable, theoretically grounded strategy for addressing spatial bias in archaeological datasets.
Sampling historical-cultural artefacts from museums and excavation sites is a delicate and critical phase inarchaeological research and the conservation of cultural heritage. This process, essential for generating scientificdata, must follow established scientific principles as well as pertinent ethical guidelines in the field. Adhering tothese principles is crucial to prevent damage to the artefacts and preserve their cultural and historical significance.Employing a descriptive-analytical approach, this study systematically examines the scientific and ethical challengesinvolved in this process, utilising library resources and the authors’ field experiences. The findings revealed thatethical and optimal sampling of historical-cultural artefacts requires the integration of three key dimensions: 1)Technical dimension, involving the selection of minimally invasive, high-precision methods and the developmentof standardised protocols for sampling; 2) Ethical dimension, encompassing adherence to the five core principlesof minimum intervention, scientific justification, transparency, accountability, and respect for stakeholders’rights; and 3) Managerial dimension, which includes establishing controlled sample repositories. These findingsunderscore the necessity of formulating national scientific and ethical sampling guidelines. Furthermore, theydemonstrate how implementing such a framework can safeguard artefacts from physical damage, enhance thepurposefulness and accuracy of sampling, prevent resource waste, reduce the frequency of sampling throughimproved access to collected data (via sample databases), and most importantly, ensure the satisfaction of currentand future stakeholders.
Yohann Perron, Vladyslav Sydorov, Adam P. Wijker
et al.
Airborne Laser Scanning (ALS) technology has transformed modern archaeology by unveiling hidden landscapes beneath dense vegetation. However, the lack of expert-annotated, open-access resources has hindered the analysis of ALS data using advanced deep learning techniques. We address this limitation with Archaeoscape (available at https://archaeoscape.ai/data/2024/), a novel large-scale archaeological ALS dataset spanning 888 km$^2$ in Cambodia with 31,141 annotated archaeological features from the Angkorian period. Archaeoscape is over four times larger than comparable datasets, and the first ALS archaeology resource with open-access data, annotations, and models. We benchmark several recent segmentation models to demonstrate the benefits of modern vision techniques for this problem and highlight the unique challenges of discovering subtle human-made structures under dense jungle canopies. By making Archaeoscape available in open access, we hope to bridge the gap between traditional archaeology and modern computer vision methods.
The Gaia mission has revolutionized our view of the Milky Way and its satellite citizens. The field of Galactic Archaeology has been piecing together the formation and evolution of the Galaxy for decades, and we have made great strides, with often limited data, towards discovering and characterizing the subcomponents of the Galaxy and its building blocks. Now, the exquisite 6D phase-space plus chemical information from Gaia and its complementary spectroscopic surveys has handed us a plethora of data to pour over as we move towards a quantitative rather than qualitative view of the Galaxy and its progenitors. We review the state of the field in the post-Gaia era, and examine the key lessons that will dictate the future direction of Galactic halo research.
Archaeological pottery documentation and study represents a crucial but time-consuming aspect of archaeology. While recent years have seen advances in digital documentation methods, vast amounts of legacy data remain locked in traditional publications. This paper introduces PyPotteryLens, an open-source framework that leverages deep learning to automate the digitisation and processing of archaeological pottery drawings from published sources. The system combines state-of-the-art computer vision models (YOLO for instance segmentation and EfficientNetV2 for classification) with an intuitive user interface, making advanced digital methods accessible to archaeologists regardless of technical expertise. The framework achieves over 97\% precision and recall in pottery detection and classification tasks, while reducing processing time by up to 5x to 20x compared to manual methods. Testing across diverse archaeological contexts demonstrates robust generalisation capabilities. Also, the system's modular architecture facilitates extension to other archaeological materials, while its standardised output format ensures long-term preservation and reusability of digitised data as well as solid basis for training machine learning algorithms. The software, documentation, and examples are available on GitHub (https://github.com/lrncrd/PyPottery/tree/PyPotteryLens).
La aplicación de estudios sistemáticos en la Sierra El Alto-Ancasti ha aportado información valiosa acerca de las distintas modalidades de ocupación por parte de las poblaciones que habitaron la zona en los últimos 2000 años. En el mismo sentido, con la presente investigación buscamos abordar una estructura de vivienda de la sierra, de manera que complemente las interpretaciones realizadas en el área hasta el momento. Para esto consideraremos la información obtenida a partir de dos líneas de evidencia aplicadas a los materiales recuperados del interior del sitio: análisis tecno-morfológico y morfológico-funcional del conjunto lítico tallado y análisis de microrrestos arqueobotánicos en contenedores cerámicos. Mediante estos estudios pretendemos conocer las prácticas cotidianas realizadas en el interior de la misma y vislumbrar las actividades que posiblemente acontecieron en las demás residencias que fueron habitadas durante el primer milenio de la era en la zona.
Guido S. Mariani, Filippo Brandolini, Rita T. Melis
Human agency on landscape modification and land use is often seen in terms of socio-economic opportunities vs. natural constraints. In the study of prehistoric cultures this is both a strong source of information about sustenance strategies and community behaviours, and a subject potentially easy to analyse within a limited set of physical and social parameters. The recent advancements in the use of spatial analysis tools in landscape archaeology allow to obtain ever more precise models. However, studies that compare at the same time the geological landscape and social elements are very scarce. We used Point Pattern Analysis and Modelling to investigate megalithic structures (nuraghes) in Bronze Age southwestern Sardinia (Italy) and identify correlations between their spatial patterns and a set of covariates encompassing both environmental (i.e. topography and geological resources) and cultural factors. The models which best represent pattern distribution come from the combination of covariates from both groups.The models highlight a close distance from known ore deposits and show a clear dependence of Nuragic populations to ore extraction and metallurgy. The availability of fertile soils with moderate permeability and moderately low pH is also significant, as well as a preference to prominent locations with a positive correlation with the Topographic Position Index and the Convexity Index. From a cultural standpoint, we observed a consistent aggregation of simple nuraghes around complex nuraghes at mid-short distances. The occurrence of polycentric patterns can be explained either by the former emerging from the presence of the latter or vice versa, and is typically associated with a loosely stratified social structure devoid of strong hierarchies. These results underscore the efficacy of spatial analysis in disentangling and juxtaposing the physical and social factors influencing the distribution of past culture, and offer new insight on the development of Bronze Age societies in their geographical context.
Ali Behnia, Mohamaad Ebrahim Zarei, Maryam Mohammadi
Monumental structures are certainly the most common public buildings in Islamic architecture, being second only to mosques. Eight such structures were recorded during the survey of Bijar County of eastern Kurdistan province. These monumental buildings tend to share common plans and building materials. Given their position on the routes linking northwestern and western Iran as well as their proximity to the major political centres of Maragheh, Soltaniyeh and Takht-e Soleyman, these buildings, apart from a memorial function, perhaps beaconed caravans along the regional routes. Yet, these structures largely remain unaddressed by any systematic work. The main objective of the present study is to publish these buildings so as to give a more refined picture of the regional route networks in the Islamic period. The comparisons and discrepancies detected between these structures in the study area and the nearby regions, notably the Zanjan plain, characterized by environmental and cultural settings almost identical to the Garrus region, can be of great help in this regard. Accordingly, the questions considered here are: 1) What factors played a role in the emergence of these monuments in the region? 2) How did previous architectural traditions affect their formation? And, 3) To what extent are these buildings effective in reconstructing the ancient routes, and where in the region do they find comparisons in form and building materials? Social, religious and political factors have informed the development of towers in the region during the Seljuk and Ilkhanid rules. Adjacency to major coeval political centres, safety of the routes thanks to vigorous local rulers, and favorable environmental conditions (access to water and the presence of numerous villages along the routes) are the most remarkable of such factors. Previous traditions and modeling on earlier standing towers from the historical (Sassanian) and Islamic periods played a notable part in the construction of the regional guidance towers. Affinities to the standing structures in the neighboring regions, including the Khoein Tower, the mausoleum of the Prophet Qeydar, the tomb tower at Kahriz Siah Mansur (Ijrud) in Zanjan province, and their comparisons with the monumental structures of the Bijar region, apart from contributing to the reconstruction of the past route networks, attest to their original function as navigational aid. The study adapts a historical-descriptive approach and builds on field surveys, documentation in photo, and looking up related information in historical texts and library documents.
Archaeology can be broadly defined as the study and interpretation of the past through material remains. Videogame worlds, though immaterial in nature, can also afford opportunities to study the people who existed within them based on what they leave behind. In this paper we present the first formal archaeological survey of a predominantly single-player game, by examining the player-generated content that is asynchronously distributed to players in the videogame Elden Ring.
Alex Brandsen, Suzan Verberne, Karsten Lambers
et al.
This paper presents AGNES, the first information retrieval system for archaeological grey literature, allowing full-text search of these long archaeological documents. This search system has a web interface that allows archaeology professionals and scholars to search through a collection of over 60,000 Dutch excavation reports, totalling 361 million words. We conducted a user study for the evaluation of AGNES's search interface, with a small but diverse user group. The evaluation was done by screen capturing and a think aloud protocol, combined with a user interface feedback questionnaire. The evaluation covered both controlled use (completion of a pre-defined task) as well as free use (completion of a freely chosen task). The free use allows us to study the information needs of archaeologists, as well as their interactions with the search system. We conclude that: (1) the information needs of archaeologists are typically recall-oriented, often requiring a list of items as answer; (2) the users prefer the use of free-text queries over metadata filters, confirming the value of a free-text search system; (3) the compilation of a diverse user group contributed to the collection of diverse issues as feedback for improving the system. We are currently refining AGNES's user interface and improving its precision for archaeological entities, so that AGNES will help archaeologists to answer their research questions more effectively and efficiently, leading to a more coherent narrative of the past.
Alex Brandsen, Suzan Verberne, Karsten Lambers
et al.
The amount of archaeological literature is growing rapidly. Until recently, these data were only accessible through metadata search. We implemented a text retrieval engine for a large archaeological text collection ($\sim 658$ Million words). In archaeological IR, domain-specific entities such as locations, time periods, and artefacts, play a central role. This motivated the development of a named entity recognition (NER) model to annotate the full collection with archaeological named entities. In this paper, we present ArcheoBERTje, a BERT model pre-trained on Dutch archaeological texts. We compare the model's quality and output on a Named Entity Recognition task to a generic multilingual model and a generic Dutch model. We also investigate ensemble methods for combining multiple BERT models, and combining the best BERT model with a domain thesaurus using Conditional Random Fields (CRF). We find that ArcheoBERTje outperforms both the multilingual and Dutch model significantly with a smaller standard deviation between runs, reaching an average F1 score of 0.735. The model also outperforms ensemble methods combining the three models. Combining ArcheoBERTje predictions and explicit domain knowledge from the thesaurus did not increase the F1 score. We quantitatively and qualitatively analyse the differences between the vocabulary and output of the BERT models on the full collection and provide some valuable insights in the effect of fine-tuning for specific domains. Our results indicate that for a highly specific text domain such as archaeology, further pre-training on domain-specific data increases the model's quality on NER by a much larger margin than shown for other domains in the literature, and that domain-specific pre-training makes the addition of domain knowledge from a thesaurus unnecessary.
Until now, the well-known Kurgans in northwestern Iran were associated with burial mounds containing burial pits;however, discoveries in 2018 revealed mounds lacking human burials indicating still unknown rituals and ceremonies.Shahliq Kurgan, 178 km northeast of Tabriz, is one of such Kurgans. Before the construction of Peygham-Chay Damby East Azerbaijan Regional Water Authority, the survey and identification of archaeological sites at the dam sitewas done in 2014 in order to save the historical-cultural monuments at risk of being submerged. The first season ofrescue excavation began in 2018. The architecture of the mound, abundant stone tools, sacrificial offerings as wellas ash deposits, indicate that the mound had been a place for some special rituals and ceremonies during the earlyfirst millennium BCE. The ash material recovered from the site suggested the tradition of cremation, a hypothesisrejected in later anthropological experiments. It may also be one of the first sites where fire was set in an openspace for ritual purposes, since the large volume of ash could be evidence for this idea. The evidences for ecologicalsequence obtained from deposits underneath a stone structure indicate that during the period of establishment ofhuman settlements in Bronze Age, metal extraction and smelting and extensive use of forest resources caused thevegetation to turn from dense forests into scattered shrubs. The present study is based on field excavations as wellas library resources to study the function of burial-deprived kurgans following a descriptive analytic approach.
We present a zooarchaeological analysis of the faunal record of Los Viscos site [SCatBe6(1)], located in El Bolsón Valley, Belén Department, Catamarca province. The faunal assemblage was recovered in layers 1 and 1a, corres-ponding to the Late prehispanic and Hispanic-Indigenous periods, respectively. Camelids seem to have been the main resource, and wild minor fauna was marginally exploited. Consumption of camelids was focused on meat and marrow, and meat delayed consumption through drying is probable to have occurred in the Late prehispanic occu-pation. Comparisons with data from earlier occupations of the site suggest the continuity of the predominance of camelids, their age profiles and anatomical distribution. However, evidence of processing of other fauna is restric-ted to the latest occupations presented here.
The reviewed publication, published in 2019 by the British publishing house Archaeopress, is a collection of texts based on papers and posters presented at the international conference under the same title held in Prague in April 2018. This meeting brought together archaeologists from many European countries – including Croatia, Czechia, Germany, Norway, Poland, Portugal, Russia, Slovakia, Switzerland, Italy, and Hungary – who conduct research on the early-modern period and the pertaining material culture. Both this event and the book in question were a response to the needs of the academic community, due to the ongoing development of historical archaeology in Europe and an increase in research on artefacts and other evidence recovered during fieldwork related to this. The time-frame of the post-medieval period differs slightly across particular European countries, encompassing artefacts from between the 15th and 18th centuries.