The paper entitled “Probabilistic Modelling using Monte Carlo Simulation for Incorporating Uncertainty in Least Cost Path Results: a Roman Road Case Study” [1] submitted by J. Lewis presents an innovative approach to applying Least Cost Path (LCP) analysis to incorporate uncertainty of the Digital Elevation Model used as the topographic surface on which the path is calculated.

The proposition of using Monte Carlo simulations to produce numerous LCP, each with a slightly different DEM included in the error range of the model, allows one to strengthen the method by proposing a probabilistic LCP rather than a single and arbitrary one which does not take into account the uncertainty of the topographic reconstruction. This new method is integrated in the R package leastcostpath [2].

The author tests the method using a Roman road built along a ridge in Cumbria, England. The integration of the uncertainty of the DEM, thanks to Monte Carlo simulations, shows that two paths could have the same probability to be the real LCP. One of them is indeed the path that the Roman road took. In particular, it is one of two possibilities of LCP in the south to north direction.

This new probabilistic method therefore strengthens the reconstruction of past pathways, while also allowing new hypotheses to be tested, and, in this case study, to suggest that the northern part of the Roman road’s location was selected to help the northward movements.

[1] Lewis, J., 2020. Probabilistic Modelling using Monte Carlo Simulation for Incorporating Uncertainty in Least Cost Path Results: a Roman Road Case Study. SocArXiv, mxas2, ver 17 peer-reviewed and recommended by PCI Archaeology, 10.31235/osf.io/mxas2.

[2] Lewis, J., 2020. leastcostpath: Modelling Pathways and Movement Potential Within a Landscape. R package. Version 1.7.4.

Proteomics is an increasingly applied field of study in archaeology. The characterisation of proteins in ancient biomaterials has been used extensively to determine the sex of certain animals (from dental enamel) or to identify species from non-diagnostic bone pieces or fragments of organic materials (glues and residues, for example). Paleoproteomics has been accompanied by methodological developments, in particular to reduce the size of samples affected by destructive analyses and to refine the level of species determination. The article by Joannes Dekker and colleagues (2024) - "Palaeoproteomic identification of a whale bone tool from Bronze Age Heiloo, the Netherlands" - provides a relevant and innovative example, incorporating ZooMS and SPIN techniques as well as the creation of a database of new reference collagens (cetaceans) specific to the site's natural environment (North Sea coast). The interest of this study also lies in the contribution of a use-wear analysis carried out prior to the sampling. This comparison of multidisciplinary data is essential for understanding the links between man and his natural environment and the technical and economic production that is closely linked to it. The tool studied (ca. 1500 BCE) comes from a coastal Bronze Age site in the Netherlands, where the economy was highly diversified, involving the exploitation of wild and domestic animals in both terrestrial and marine environments. The study shows that the bone of a North Atlantic right whale (Eubalaena glacialis) was shaped into a tool that was probably used to process plant fibres. This discovery supports other studies highlighting the intensive and non-opportunistic exploitation of whales in the North Sea since the Pleistocene.

Dekker, J. A. A., Mylopotamitaki, D., Verbaas, A., Sinet-Mathiot, V., Presslee, S., McCarthy, M. L., Olsen, M. T., Olsen, J. V., van den Hurk, Y., Brattinga, J. & Welker, F. (2024) Palaeoproteomic identification of a whale bone tool from Bronze Age Heiloo, the Netherlands. BioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Archaeology.  https://doi.org/10.1101/2024.04.15.589626

Studies of the economy of the Roman Empire have become increasingly interdisciplinary and nuanced in recent years, allowing the discipline to make great strides in data collection and importantly in the methods through which this increasing volume of data can be effectively and meaningfully analysed [see for example 1 and 2]. One of the key aspects of modelling the ancient economy is understanding movement and transport costs, and how these facilitated trade, communication and economic development. With archaeologists adopting more computational techniques and utilising GIS analysis beyond simply creating maps for simple visualisation, understanding and modelling the costs of traversing archaeological landscapes has become a much more fruitful avenue of research. Classical archaeologists are often slower to adopt these new computational techniques than others in the discipline. This is despite (or perhaps due to) the huge wealth of data available and the long period of time over which the Roman economy developed, thrived and evolved. This all means that the Roman Empire is a particularly useful proving ground for testing and perfecting new methodological developments, as well as being a particularly informative period of study for understanding ancient human behaviour more broadly. This paper by Page [3] then, is well placed and part of a much needed and growing trend of Roman archaeologists adopting these computational approaches in their research. 

Page’s methodology builds upon De Soto’s earlier modelling of transport costs [4] and applies it in a new setting. This reflects an important practice which should be more widely adopted in archaeology. That of using existing, well documented methodologies in new contexts to offer wider comparisons. This allows existing methodologies to be perfected and tested more robustly without reinventing the wheel. Page does all this well, and not only builds upon De Soto’s work, but does so using a case study that is particularly interesting with convincing and significant results. 

As Page highlights, Northern Italy is often thought of as relatively isolated in terms of economic exchange and transport, largely due to the distance from the sea and the barriers posed by the Alps and Apennines. However, in analysing this region, and not taking such presumptions for granted, Page quite convincingly shows that the waterways of the region played an important role in bringing down the cost of transport and allowed the region to be far more interconnected with the wider Roman world than previous studies have assumed.  

This article is clearly a valuable and important contribution to our understanding of computational methods in archaeology as well as the economy and transport network of the Roman Empire. The article utilises innovative techniques to model transport in an area of the Roman Empire that is often overlooked, with the economic isolation of the area taken for granted. Having high quality research such as this specifically analysing the region using the most current methodologies is of great importance. Furthermore, developing and improving methodologies like this allow for different regions and case studies to be analysed and directly compared, in a way that more traditional analyses simply cannot do. As such, Page has demonstrated the importance of reanalysing traditional assumptions using the new data and analyses now available to archaeologists. 

References

[1] Brughmans, T. and Wilson, A. (eds.) (2022). Simulating Roman Economies: Theories, Methods, and Computational Models. Oxford. 

[2] Dodd, E.K. and Van Limbergen, D. (eds.) (2024). Methods in Ancient Wine Archaeology: Scientific Approaches in Roman Contexts. London ; New York. 

[3] Page, J. (2024). Rivers vs. Roads? A route network model of transport infrastructure in Northern Italy during the Roman period, Zenodo, 7971399, ver. 3 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7971399

[4] De Soto P (2019). Network Analysis to Model and Analyse Roman Transport and Mobility. In: Finding the Limits of the Limes. Modelling Demography, Economy and Transport on the Edge of the Roman Empire. Ed. by Verhagen P, Joyce J, and Groenhuijzen M. Springer Open Access, pp. 271–90. https://doi.org/10.1007/978-3-030-04576-0_13

The paper entitled “Comparing summed probability distributions of shoreline and radiocarbon dates from the Mesolithic Skagerrak coast of Norway” by Isak Roalkvam and Steinar Solheim (2024) sheds new light on the degree to which shoreline dating may be used as a reliable chronological and palaeodemographic proxy in the Mesolthic of southern Norway.

Based on geologically motivated investigations of eustatic and isostatic sea-level changes, shoreline dating has long been used as a method to date archaeological sites in Scandinavia, not least in Norway (e.g., Bjerck 2008; Astrup 2018). Establishing reliable sea-level curves requires much effort and variations across regions may be substantial. While this topic has seen a great deal of attention in Norway specifically, many purely geological questions remain. In addition, dating archaeological sites by linking their elevation to previously established seal-level curves relies strongly on the foundational assumption that such sites were in fact shore-bound. Given the strong contrast between terrestrial and marine productivity in high-latitude regions such as Norway, this assumption per se is not unreasonable. It is very likely that the sea has played a decisive role in the lives of Stone Age peoples throughout (Persson et al. 2017), just as it has in later periods here. However, many confounding factors relating to both taphonomy and human behaviour are also likely to have loosened the shore/site relationship. Systematic variations driven by cultural norms about settlement location, mobility, as well as factors such as shelter construction, fuel use and a range of other possible factors could variously have impacted the validity or at least the precision of shoreline dating.

By developing a new methodology for handling and assessing a large number of shoreline dated sites, Roalkvam and Solheim use state-of-the-art Bayesian statistical methods to compare shoreline and radiocarbon dates as proxies for population activity. The probabilistic treatment of shoreline dates in this way is novel, and the divergences between the two data sets are interpreted by the authors in light of specific behavioural, cultural, and demographic changes. Many of the peaks and troughs observed in these time-series may be interpreted in light of long-observed cultural transitions while others may relate to population dynamics now also visible in palaeogenomic analyses (Günther et al. 2018; Manninen et al. 2021). Overall, this paper makes an innovative and fresh contribution to the use of shoreline dating in Norwegian archaeology, specifically by articulating it with recent developments in Open Science and data-driven approaches to archaeological questions (Marwick et al. 2017).

References

Astrup, P. M. 2018. Sea-Level Change in Mesolithic Southern Scandinavia : Long- and Short-Term Effects on Society and the Environment. Aarhus: Aarhus University Press.

Bjerck, H. B. 2008. Norwegian Mesolithic Trends: A Review. In Mesolithic Europe, edited by Geoff Bailey and Penny Spikins, 60–106. Cambridge: Cambridge University Press.

Günther, T., Malmström, H., Svensson, E. M., Omrak, A., Sánchez-Quinto, F., Kılınç, G. M., Krzewińska, M. et al. 2018. Population Genomics of Mesolithic Scandinavia: Investigating Early Postglacial Migration Routes and High-Latitude Adaptation. PLOS Biology 16 (1): e2003703. https://doi.org/10.1371/journal.pbio.2003703

Manninen, M. A., Damlien, H., Kleppe, J. I., Knutsson, K., Murashkin, A., Niemi, A. R., Rosenvinge, C. S. and Persson, P. 2021. First Encounters in the North: Cultural Diversity and Gene Flow in Early Mesolithic Scandinavia. Antiquity 95 (380): 310–28. https://doi.org/10.15184/aqy.2020.252

Marwick, B., d’Alpoim Guedes, J. A., Barton, C. M., Bates, L. A., Baxter, M., Bevan, A., Bollwerk, E. A. et al. 2017. Open Science in Archaeology. The SAA Archaeological Record 17 (4): 8–14. https://doi.org/10.31235/osf.io/72n8g

Persson, P., Riede, F., Skar, B., Breivik, H. M. and Jonsson, L. 2017. The Ecology of Early Settlement in Northern Europe: Conditions for Subsistence and Survival. Sheffield: Equinox.

Roalkvam, I. and Solheim, S. (2024). Comparing summed probability distributions of shoreline and radiocarbon dates from the Mesolithic Skagerrak coast of Norway, SocArXiv, 2f8ph, ver. 5 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.31235/osf.io/2f8ph

This recommended paper on the IUENNA project (Hagmann and Reiner 2023) is not a paper in the traditional sense, but it is a reworked version of a project proposal. It is refreshing to read about a project that has just started and see what the aims of the project are. This ties in with several open science ideas and standards (e.g. Brinkman et al. 2023). I am looking forward to see in a few years how the authors managed to reach the aims and goals of the project.

The IUENNA project deals with the legacy data and old excavations on the Hemmaberg and in the Jauntal. Archaeological research in this small, but important region, has taken place for more than a century, revealing material from over 2000 years of human history. The Hemmaberg is well known for its late antique and early medieval structures, such as roads, villas and the various churches. The wider Jauntal reveals archaeological finds and features dating from the Iron Age to the recent past. The authors of the paper show the need to make sure that the documentation and data of these past archaeological studies and projects will be accessible in the future, or in their own words: "Acute action is needed to systematically transition these datasets from physical filing cabinets to a sustainable, networked virtual environment for long-term use" (Hagmann and Reiner 2023: 5).

The papers clearly shows how this initiative fits within larger developments in both Digital Archaeology and the Digital Humanities. In addition, the project is well grounded within Austrian archaeology. While the project ties in with various international standards and initiatives, such as Ariadne (https://ariadne-infrastructure.eu/) and FAIR-data standards (Wilkinson et al. 2016, 2019), it would benefit from the long experience institutes as the ADS (https://archaeologydataservice.ac.uk/) and DANS (see Data Station Archaeology: https://dans.knaw.nl/en/data-stations/archaeology/) have on the storage of archaeological data. I would also like to suggest to have a look at the Dutch SIKB0102 standard (https://www.sikb.nl/datastandaarden/richtlijnen/sikb0102) for the exchange of archaeological data. The documentation is all in Dutch, but we wrote an English paper a few years back that explains the various concepts (Boasson and Visser 2017). However, these are a minor details or improvements compared to what the authors show in their project proposal. The integration of many standards in the project and the use of open software in a well-defined process is recommendable.

The IUENNA project is an ambitious project, which will hopefully lead to better insights, guidelines and workflows on dealing with legacy data or documentation. These lessons will hopefully benefit archaeology as a discipline. This is important, because various (European) countries are dealing with similar problem, since many excavations of the past have never been properly published, digitalized or deposited. In the Netherlands, for example, various projects dealt with publication of legacy excavations in the Odyssee-project (https://www.nwo.nl/onderzoeksprogrammas/odyssee). This has led to the publication of various books and datasets (24) (https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:34359), but there are still many datasets (8) missing from the various projects. In addition, each project followed their own standards in creating digital data, while IUENNA will make an effort to standardize this. There are still more than 1000 Dutch legacy excavations still waiting to be published and made into a modern dataset (Kleijne 2010) and this is probably the case in many other countries. I sincerely hope that a successful end of IUENNA will be an inspiration for other regions and countries for future safekeeping of legacy data.

References

Boasson, W and Visser, RM. 2017 SIKB0102: Synchronizing Excavation Data for Preservation and Re-Use. Studies in Digital Heritage 1(2): 206–224. https://doi.org/10.14434/sdh.v1i2.23262

Brinkman, L, Dijk, E, Jonge, H de, Loorbach, N and Rutten, D. 2023 Open Science: A Practical Guide for Early-Career Researchers https://doi.org/10.5281/zenodo.7716153

Hagmann, D and Reiner, F. 2023 IUENNA – openIng the soUthErn jauNtal as a micro-regioN for future Archaeology: A ‘para-description’. https://doi.org/10.31219/osf.io/5vwg8

Kleijne, JP. 2010. Odysee in de breedte. Verslag van het NWO Odyssee programma, kortlopend onderzoek: ‘Odyssee, een oplossing in de breedte: de 1000 onuitgewerkte sites, die tot een substantiële kennisvermeerdering kunnen leiden, digitaal beschikbaar!’ ‐ ODYK‐09‐13. Den Haag: E‐depot Nederlandse Archeologie (EDNA). https://doi.org/10.17026/dans-z25-g4jw

Wilkinson, MD, Dumontier, M, Aalbersberg, IjJ, Appleton, G, Axton, M, Baak, A, Blomberg, N, Boiten, J-W, da Silva Santos, LB, Bourne, PE, Bouwman, J, Brookes, AJ, Clark, T, Crosas, M, Dillo, I, Dumon, O, Edmunds, S, Evelo, CT, Finkers, R, Gonzalez-Beltran, A, Gray, AJG, Groth, P, Goble, C, Grethe, JS, Heringa, J, ’t Hoen, PAC, Hooft, R, Kuhn, T, Kok, R, Kok, J, Lusher, SJ, Martone, ME, Mons, A, Packer, AL, Persson, B, Rocca-Serra, P, Roos, M, van Schaik, R, Sansone, S-A, Schultes, E, Sengstag, T, Slater, T, Strawn, G, Swertz, MA, Thompson, M, van der Lei, J, van Mulligen, E, Velterop, J, Waagmeester, A, Wittenburg, P, Wolstencroft, K, Zhao, J and Mons, B. 2016 The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3(1): 160018. https://doi.org/10.1038/sdata.2016.18

Wilkinson, MD, Dumontier, M, Jan Aalbersberg, I, Appleton, G, Axton, M, Baak, A, Blomberg, N, Boiten, J-W, da Silva Santos, LB, Bourne, PE, Bouwman, J, Brookes, AJ, Clark, T, Crosas, M, Dillo, I, Dumon, O, Edmunds, S, Evelo, CT, Finkers, R, Gonzalez-Beltran, A, Gray, AJG, Groth, P, Goble, C, Grethe, JS, Heringa, J, Hoen, PAC ’t, Hooft, R, Kuhn, T, Kok, R, Kok, J, Lusher, SJ, Martone, ME, Mons, A, Packer, AL, Persson, B, Rocca-Serra, P, Roos, M, van Schaik, R, Sansone, S-A, Schultes, E, Sengstag, T, Slater, T, Strawn, G, Swertz, MA, Thompson, M, van der Lei, J, van Mulligen, E, Jan Velterop, Waagmeester, A, Wittenburg, P, Wolstencroft, K, Zhao, J and Mons, B. 2019 Addendum: The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 6(1): 6. https://doi.org/10.1038/s41597-019-0009-6