The paper “A Focus on the Future of our Tiny Piece of the Past: Digital Archiving of a Long-term Multi-participant Regional Project” (Madry et al., 2023) describes practices, challenges and opportunities encountered in digital archiving of a landscape research project running in Burgundy, France for more than 45 years. As an unusually long-running multi-disciplinary undertaking working with a large variety of multi-modal digital and non-digital data, the Burgundy project has lived through the development of documentation and archiving technologies from the 1970s until today and faced many of the challenges relating to data management, preservation and migration.

The major strenght of the paper is that it provides a detailed description of the evolution of digital data archiving practices in the project including considerations about why some approaches were tested and abandoned. This differs from much of the earlier literature where it has been more common to describe individual solutions how digital archiving was either planned or was performed at one point of time. A longitudinal description of what was planned, how and why it has worked or failed so far, as described in the paper, provides important insights in the everyday hurdles and ways forward in digital archiving. As a description of a digital archiving initiative, the paper makes a valuable contribution for the data archiving scholarship as a case description of practices and considerations in one research project. For anyone working with data management in a research project either as a researcher or data manager, the text provides useful advice on important practical matters to consider ahead, during and after the project. The main advice the authors are giving, is to plan and act for data preservation from the beginning of the project rather than doing it afterwards. To succeed in this, it is crucial to be knowledgeable of the key concepts of data management—such as “digital data fixity, redundant backups, paradata, metadata, and appropriate keywords” as the authors underline—including their rationale and practical implications. The paper shows also that when and if unexpected issues raise, it is important to be open for different alternatives, explore ways forward, and in general be flexible.

The paper makes also a timely contribution to the discussion started at the session “Archiving information on archaeological practices and work in the digital environment: workflows, paradata and beyond” at the Computer Applications and Quantitative 2023 conference in Amsterdam where it was first presented. It underlines the importance of understanding and communicating the premises and practices of how data was collected (and made) and used in research for successful digital archiving, and the similar pertinence of documenting digital archiving processes to secure the keeping, preservation and effective reuse of digital archives possible.

References

Madry, S., Jansen, G., Murray, S., Jones, E., Willcoxon, L. and Alhashem, E. (2023) A Focus on the Future of our Tiny Piece of the Past: Digital Archiving of a Long-term Multi-participant Regional Project, Zenodo, 7967035, ver. 3 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7967035

In this paper (Linsel/Bullenkamp/Mara 2024), the authors propose an automatic system for scar-ridge-pattern detection on palaeolithic artefacts based on Morse Theory. Scare-Ridge pattern recognition is a process that is usually done manually while creating a drawing of the object itself. Automatic systems to detect scars or ridges exist, but only a small amount of them is utilizing 3D data. In addition to the scar-ridges detection, the authors also experiment in automatically detecting the operational sequence, the temporal relation between scars and ridges. As a result, they can export a traditional drawing as well as graph models displaying the relationships between the scars and ridges.

After an introduction to the project and the practice of documenting palaeolithic artefacts, the authors explain their procedure in automatising the analysis of scars and ridges as well as their temporal relation to each other on these artefacts. To illustrate the process, an open dataset of lithic artefacts from the Grotta di Fumane, Italy, was used and 62 artefacts selected. To establish a Ground Truth, the artefacts were first annotated manually. The authors then continue to explain in detail each step of the automated process that follows and the results obtained.

In the second part of the paper, the results are presented. First the results of the segmentation process shows that the average percentage of correctly labelled vertices is over 91%, which is a remarkable result. The graph modelling however shows some more difficulties, which the authors are aware of. To enhance the process, the authors rightfully aim to include datasets of experimental archaeology in the future. They also aim to develop a way of detecting the operational sequence automatically and precisely.

This paper has great potential as it showcases exactly what Digital and Computational Archaeology is about: The development of new digital methods to enhance the analysis of archaeological data. While this procedure is still in development, the authors were able to present a valuable contribution to the automatization of analytical archaeology. By creating a step towards the machine-readability of this data, they also open up the way to further steps in machine learning within Archaeology.

Bibliography

Linsel, F., Bullenkamp, J. P., and Mara, H. (2024). Linking Scars: Topology-based Scar Detection and Graph Modeling of Paleolithic Artifacts in 3D, Zenodo, 8296269, ver. 3 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.8296269

This well-written and interesting paper ‘Survey Planning, Allocation, Costing and Evaluation (SPACE) Project: Developing a Tool to Help Archaeologists Conduct More Effective Surveys’ deals with the development of a ‘modular, accessible, and simple web-based platform for survey planning and quality assurance’ in the area of pedestrian field survey methods (Banning et al. 2024).

Although there have been excellent treatments of statistics in archaeological field survey (among which various by the first author: Banning 2020, 2021), and there is continuous methodological debate on platforms such as the International Mediterranean Survey Workshop (IMSW), in papers dealing with the current development and state of the field (Knodell et al. 2023), good practices (Attema et al. 2020) or the merits of a quantifying approach to archaeological densities (cf. de Haas et al. 2023), this paper rightfully addresses the lack of rigorous statistical approaches in archaeological field survey. As argued by several scholars such as Orton (2000), this mainly appears the result of lack of knowledge/familiarity/resources to bring in the required expertise etc. with the application of seemingly intricate statistics (cf. Waagen 2022). In this context this paper presents a welcome contribution to the feasibility of a robust archaeological field survey design. 

The SPACE application, under development by the authors, is introduced in this paper. It is a software tool that aims to provide different modules to assist archaeologists to make calculations for sample size, coverage, stratification, etc. under the conditions of survey goals and available resources. In the end, the goal is to ensure archaeological field surveys will attain their objectives effectively and permit more confidence in the eventual outcomes. The module concerning Sweep Widths, an issue introduced by the main author in 2006 (Banning 2006) is finished; the sweep width assessment is a methodology to calibrate one’s survey project for artefact types, landscape, visibility and person-bound performance, eventually increasing the quality (comparability) of the collected samples. This is by now a well-known calibration technique, yet little used, so this effort to make that more accessible is certainly laudable. An excellent idea, and another aim of this project, is indeed to build up a database with calibration data, so applying sweep-width corrections will become easier accessible to practitioners who lack time to set up calibration exercises. 

It will be very interesting to have a closer look at the eventual platform and to see if, and how, it will be adapted by the larger archaeological field survey community, both from an academic research perspective as from a heritage management point of view. I happily recommend this paper and all debate relating to it, including the excellent peer reviews of the manuscript by Philip Verhagen and Tymon de Haas (available as part of this PCI recommendation procedure), to any practitioner of archaeological field survey.

References

Attema, P., Bintliff, J., Van Leusen, P.M., Bes, P., de Haas, T., Donev, D., Jongman, W., Kaptijn, E., Mayoral, V., Menchelli, S., Pasquinucci, M., Rosen, S., García Sánchez, J., Luis Gutierrez Soler, L., Stone, D., Tol, G., Vermeulen, F., and Vionis. A. 2020. “A guide to good practice in Mediterranean surface survey projects”, Journal of Greek Archaeology 5, 1–62. https://doi.org/10.32028/9781789697926-2

Banning, E.B., Alicia L. Hawkins, S.T. Stewart, Sweep widths and the detection of artifacts in archaeological survey, Journal of Archaeological Science, Volume 38, Issue 12, 2011, Pages 3447-3458. https://doi.org/10.1016/j.jas.2011.08.007 

Banning, E.B. 2020. Spatial Sampling. In: Gillings, M., Hacıgüzeller, P., Lock, G. (eds.) Archaeological Spatial Analysis. A Methodological Guide. Routledge.

Banning, E.B. 2021. Sampled to Death? The Rise and Fall of Probability Sampling in Archaeology. American Antiquity, 86(1), 43-60. https://doi.org/10.1017/aaq.2020.39

Banning, E. B. Steven Edwards, & Isaac Ullah. (2024). Survey Planning, Allocation, Costing and Evaluation (SPACE) Project: Developing a Tool to Help Archaeologists Conduct More Effective Surveys. Zenodo, 8072178, ver. 9 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.8072178

Knodell, A.R., Wilkinson, T.C., Leppard, T.P. et al. 2023. Survey Archaeology in the Mediterranean World: Regional Traditions and Contributions to Long-Term History. J Archaeol Res 31, 263–329 (2023). https://doi.org/10.1007/s10814-022-09175-7 

Orton, C. 2000. Sampling in Archaeology. Cambridge University Press. https://doi.org/10.1017/CBO9781139163996

Waagen, J. 2022. Sampling past landscapes. Methodological inquiries into the bias problems of recording archaeological surface assemblages. PhD-Thesis. https://hdl.handle.net/11245.1/e9cb922c-c7e4-40a1-b648-7b8065c46880 

de Haas, T., Leppard, T. P., Waagen, J., & Wilkinson, T. (2023). Myopic Misunderstandings? A Reply to Meyer (JMA 35(2), 2022). Journal of Mediterranean Archaeology, 36(1), 127-137. https://doi.org/10.1558/jma.27148

“3Duewelsteene - A website for the 3D visualization of the megalithic passage grave Düwelsteene near Heiden in Westphalia, Germany” (Tharandt 2024) presents several 3-dimensional models of the Düwelsteene monument, along with contextual information about the grave and the process of creating the models. The website (https://3duewelsteene.github.io/) includes English and German versions, making it accessible to a wide audience. The website itself serves as the primary means of presenting the data, rather than as a supplement to a written text. This is an innovative and engaging way to present the research to a wider public.

Düwelsteene (“Devil’s Stones”) is a megalithic passage grave from the Funnel Beaker culture, dating to approximately 3300 BC. to 2600 BC. that was excavated in 1932. The website displays three separate 3-dimensional models. They ares shown in the 3D viewer software 3DHOP, which enables viewers to interact with the models in several ways, Annotations on the models display further information.

The first model was created by image-based modeling and shows the monument as it appears today.

A second model uses historical photographs and excavation data to reconstruct the grave as it appeared prior to the 1932 archaeological excavation. Restoration work following the excavation relocated many of the stones. Pre-1932 photographs collected from residents of the nearby town of Heiden were then used to create a model showing what the tomb looked like before the restoration work. It is commendable that a “certainty view” of the model shows the certainty with which the stones can be put at the reconstructed place. Gaps in the 3D models of stones that were caused by overlap with other stones have been filled with a rough mesh and marked as such, thereby differentiating between known and unknown parts of the stones.

The third model is the most imaginative and most interesting. As it shows as the grave as it might have appeared in approximately 3000 B.C., many aspects of this model are necessarily somewhat speculative. There is no direct evidence for exact size and shape of the capstones, the height of the mound, and other details. But enough is known about other similar constructions to allow these details to be inferred with some confidence. Again, care was taken to enable viewers to distinguish between the stones that are still in existence and those that were reconstructed.

A video on the home page of the website adds a nice touch. It starts with the model of the Düwelsteene as it currently appears then shows, in reverse order, the changes to the grave, ending with the inferred original state.

The 3D reconstructions are convincing and the methods well described. This project follows an open science approach and the FAIR principles, which is commendable and cutting edge in the field of Digital Archaeology. The preprint of the website hosted on zenodo includes all the photos, text, html files, and nine individual 3D model (.ply) files that are combined in the reconstructions exhibited on the website. A “readme.md” file includes details about building the models using CloudCompare and Blender, and modifications to the 3D viewer software (3DHOP) to get the website to improve the display of the reconstructions. We have to note that the link between the reconstructed models and the html page does not work when the files are downloaded from zenodo and opened offline. The html pages open in the browser, and the individual ply files work fine, but the 3D models do not display on the browser page when the html files are opened offline. The online version of the website is working perfectly.

The 3Düwelsteene website combines the presentation of archaeological domain knowledge to a lay audience as well as in-depths information on the reconstruction process to make it an interesting contribution for researchers. By providing data and code for the website it also models an Open Science approach, which enables other researchers to re-use these materials. We congratulate the author on a successful reconstruction of the megalithic tomb, an admirable presentation of the archaeological work and the thoughtful outreach to a broad audience.

Bibliography
Tharandt, L., 3Duewelsteene - A website for the 3D visualization of the megalithic passage grave Düwelsteene near Heiden in Westphalia, Germany, https://3duewelsteene.github.io/, Zenodo, 7948379, ver. 4 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7948379

This is a fascinating paper for anyone interested in network analysis or the chronology and cultures of the case study, namely the Late prehistoric burial sites in Dorset, for which the author’s approach allowed a new perspective over an already deeply studied area [1]. This paper's implementation of Similarity Network Fusion (SNF) is noteworthy. This method is typically utilized within genetic research but has yet to be employed in Archaeology. SNF has the potential to benefit Archaeology due to its unique capabilities and approach significantly. 

The author exhibits a deep and thorough understanding of previous investigations concerning material and similarity networks while emphasizing the innovative nature of this particular study. The SNF approach intends to improve a lack of the most used (in Archaeology) similarity coefficient, the Brainerd-Robinson, in certain situations, mainly in heterogenous and noisy datasets containing a small number of samples but a large number of measurements, scale differences, and collection biases, among other things. The SNF technique, demonstrated in the case study, effectively incorporates various similarity networks derived from different datatypes into one network. 

As shown during the Dorset case study, the SNF application has a great application in archaeology, even in already available data, allowing us to go further and bring new visions to the existing interpretations. As stated by the author, SNF shows its potential for other applications and fields in archaeology coping with similar datasets, such as archaeobotany or archaeozoology, and seems to complement different multivariate statistical approaches, such as correspondence or cluster analysis.

This paper has been subject to two excellent revisions, which the author mostly accepted. One of the revisions was more technical, improving the article in the metadata part, data availability and clarification, etc. Although the second revision was more conceptual and gave some excellent technical inputs, it focused more on complementary aspects that will allow the paper to reach a wider audience. I vividly recommend its publication.

References

[1] Geitlinger, T. (2024). Similarity Network Fusion: Understanding Patterns and their Spatial Significance in Archaeological Datasets. Zenodo, 7998239, ver. 3 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7998239