​The paper “Percolation Package – From Script Sharing to Package Publication” by Sophie C. Schmidt and Simon Maddison (2023) describes the development of an R package designed to apply Percolation Analysis to archaeological spatial data. In an earlier publication, Maddison and Schmidt (2020) describe Percolation Analysis and provide case studies that demonstrate its usefulness at different spatial scales. In the current paper, the authors use their experience collaborating to develop the R package as part of a broader argument for the importance of code sharing to the research process. 

The paper begins by describing the development process of the R package, beginning with borrowing code from a geographer, refining it to fit archaeological case studies, and then collaborating to further refine and systematize the code into an R package that is more easily reusable by other researchers. As the review by Joe Roe noted, a strength of the paper is “presenting the development process as it actually happens rather than in an idealized form.” The authors also include a section about the lessons learned from their experience. 

Moving on from the anecdotal data of their own experience, the authors also explore code sharing practices in archaeology by briefly examining two datasets. One dataset comes from “open-archaeo” (https://open-archaeo.info/), an on-line list of open-source archaeological software maintained by Zack Batist. The other dataset includes articles published between 2018 and 2023 in the Journal of Computer Applications in Archaeology. Schmidt and Maddison find that these two datasets provide contrasting views of code sharing in archaeology: many of the resources in the open-archaeo list are housed on Github, lack persistent object identifiers, and many are not easily findable (other than through the open-archaeo list). Research software attached to the published articles, on the other hand, is more easily findable either as a supplement to the published article, or in a repository with a DOI.

The examination of code sharing in archaeology through these two datasets is preliminary and incomplete, but it does show that further research into archaeologists’ code-writing and code-sharing practices could be useful. Archaeologists often create software tools to facilitate their research, but how often?  How often is research software shared with published articles? How much attention is given to documentation or making the software usable for other researchers? What are best (or good) practices for sharing code to make it findable and usable? Schmidt and Maddison’s paper provides partial answers to these questions, but a more thorough study of code sharing in archaeology would be useful. Differences among journals in how often they publish articles with shared code, or the effects of age, gender, nationality, or context of employment on attitudes toward code sharing seem like obvious factors for a future study to consider.

Shared code that is easy to find and easy to use benefits the researchers who adopt code written by others, but code authors also have much to gain by sharing. Properly shared code becomes a citable research product, and the act of code sharing can lead to productive research collaborations, as Schmidt and Maddison describe from their own experience. The strength of this paper is the attention it brings to current code-sharing practices in archaeology. I hope the paper will also help improve code sharing in archaeology by inspiring more archaeologists to share their research code so other researchers can find and use (and cite) it. 

References

Maddison, M.S. and Schmidt, S.C. (2020). Percolation Analysis – Archaeological Applications at Widely Different Spatial Scales. Journal of Computer Applications in Archaeology, 3(1), p.269–287. https://doi.org/10.5334/jcaa.54 

Schmidt, S. C., and Maddison, M. S. (2023). Percolation Package - From script sharing to package publication, Zenodo, 7966497, ver. 3 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7966497

In a recent article, Fumihiro Sakahira and Hiro'omi Tsumura (2023) used social network analysis methods to analyze change in obsidian trade networks in Japan throughout the 13,000-year-long Jomon period. In the paper recommended here (Sakahira and Tsumura 2024), Social Network Analysis of Ancient Japanese Obsidian Artifacts Reflecting Sampling Bias Reduction they revisit that data and describe additional analyses that confirm the robustness of their social network analysis. The data, analysis methods, and substantive conclusions of the two papers overlap; what this new paper adds is a detailed examination of the data and methods, including use of bootstrap analysis to demonstrate the reasonableness of the methods they used to group sites into clusters.

Both papers begin with a large dataset of approximately 21,000 artifacts from more than 250 sites dating to various times throughout the Jomon period. The number of sites and artifacts, varying sample sizes from the sites, as well as the length of the Jomon period, make interpretation of the data challenging. To help make the data easier to interpret and reduce problems with small sample sizes from some sites, the authors assign each site to one of five sub-periods, then define spatial clusters of sites within each period using the DBSCAN algorithm. Sites with at least three other sites within 10 km are joined into clusters, while sites that lack enough close neighbors are left as isolates. Clusters or isolated sites with sample sizes smaller than 30 were dropped, and the remaining sites and clusters became the nodes in the networks formed for each period, using cosine similarities of obsidian assemblages to define the strength of ties between clusters and sites.

The main substantive result of Sakahira and Tsumura’s analysis is the demonstration that, during the Middle Jomon period (5500-4500 cal BP), clusters and isolated sites were much more connected than before or after that period. This is largely due to extensive distribution of obsidian from the Kozu-shima source, located on a small island off the Japanese mainland. Before the Middle Jomon period, Kozu-shima obsidian was mostly found at sites near the coast, but during the Middle Jomon, a trade network developed that took Kozu-shima obsidian far inland. This ended after the Middle Jomon period, and obsidian networks were less densely connected in the late and last Jomon periods.

The methods and conclusions are all previously published (Sakahira and Tsumura 2023). What Sakahira and Tsumura add in Social Network Analysis of Ancient Japanese Obsidian Artifacts Reflecting Sampling Bias Reduction are:

·       an examination of the distribution of cosine similarities between their clusters for each period

·       a similar evaluation of the cosine similarities within each cluster (and among the unclustered sites) for each period

·       bootstrap analyses of the mean cosine similarities and network densities for each time period

These additional analyses demonstrate that the methods used to cluster sites are reasonable, and that the use of spatially defined clusters as nodes (rather than the individual sites within the clusters) works well as a way of reducing bias from small, unrepresentative samples. An alternative way to reduce that bias would be to simply drop small assemblages, but that would mean ignoring data that could usefully contribute to the analysis.

The cosine similarities between clusters show patterns that make sense given the results of the network analysis. The Middle Jomon period has, on average, the highest cosine similarities between clusters, and most cluster pairs have high cosine similarities, consistent with the densely connected, spatially expansive network from that time period. A few cluster pairs in the Middle Jomon have low similarities, apparently representing comparisons including one of the few nodes on the margins on the network that had little or no obsidian from the Kozu-shima source. The other four time periods all show lower average inter-cluster similarities and many cluster pairs have either high or low similarities. This probably reflects the tendency for nearby clusters to have very similar obsidian assemblages to each other and for geographically distant clusters to have dissimilar obsidian assemblages. The pattern is consistent with the less densely connected networks and regionalization shown in the network graphs. Thinking about this pattern makes me want to see a plot of the geographic distances between the clusters against the cosine similarities. There must be a very strong correlation, but it would be interesting to know whether there are any cluster pairs with similarities that deviate markedly from what would be predicted by their geographic separation.

The similarities within clusters are also interesting. For each time period, almost every cluster has a higher average (mean and median) within-cluster similarity than the similarity for unclustered sites, with only two exceptions. This is partial validation of the method used for creating the spatial clusters; sites within the clusters are at least more similar to each other than unclustered sites are, suggesting that grouping them this way was reasonable.

Although Sakahira and Tsumura say little about it, most clusters show quite a wide range of similarities between the site pairs they contain; average within-cluster similarities are relatively high, but many pairs of sites in most clusters appear to have low similarities (the individual values are not reported, but the pattern is clear in boxplots for the first four periods). There may be value in further exploring the occurrence of low site-to-site similarities within clusters. How often are they caused by small sample sizes? Clusters are retained in the analysis if they have a total of at least 30 artifacts, but clusters may contain sites with even smaller sample sizes, and small samples likely account for many of the low similarity values between sites in the same cluster. But is distance between sites in a cluster also a factor? If the most distant sites within a spatially extensive cluster are dissimilar, subdividing the cluster would likely improve the results. Further exploration of these within-cluster site-to-site similarity values might be worth doing, perhaps by plotting the similarities against the size of the smallest sample included in the comparison, as well as by plotting the cosine similarity against the distance between sites. Any low similarity values not attributable to small sample sizes or geographic distance would surely be worth investigating further.

Sakahira and Tsumura also use a bootstrap analysis to simulate, for each time period, mean cosine similarities between clusters and between site pairs without clustering. They also simulate the network density for each time period before and after clustering. These analyses show that, almost always, mean simulated cosine similarities and mean simulated network density are higher after clustering than before. The simulated mean values also match the actual mean values better after clustering than before. This improved match to actual values when the sites are clustered for the bootstrap reinforces the argument that clustering the sites for the network analysis was a reasonable result.

The strength of this paper is that Sakahira and Tsumura return to reevaluate their previously published work, which demonstrated strong patterns through time in the nature and extent of Jomon obsidian trade networks. In the current paper they present further analyses demonstrating that several of their methodological decisions were reasonable and their results are robust. The specific clusters formed with the DBSCAN algorithm may or may not be optimal (which would be unreasonable to expect), but the authors present analyses showing that using spatial clusters does improve their network analysis. Clustering reduces problems with small sample sizes from individual sites and simplifies the network graphs by reducing the number of nodes, which makes the results easier to interpret.

Reference

Sakahira, F. and Tsumura, H. (2023). Tipping Points of Ancient Japanese Jomon Trade Networks from Social Network Analyses of Obsidian Artifacts. Frontiers in Physics 10:1015870. https://doi.org/10.3389/fphy.2022.1015870

Sakahira, F. and Tsumura, H. (2024). Social Network Analysis of Ancient Japanese Obsidian Artifacts Reflecting Sampling Bias Reduction, Zenodo, 10057602, ver. 7 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7969330

Tsaknaki et al. (2023) discuss a work-in-progress project in which the presentation of Cultural Heritage is communicated using Serious Games techniques in a story-centric immersive narration instead of an exhibit-centered presentation with the use of Gamification, Augmented and Virtual Reality technologies. In the introduction the authors present the project called ECHOES, in which knowledge about the past of Thessaloniki, Greece is planned to be processed as an immersive and interactive experience. After presenting related work and the methodology, the authors describe the proposed design of the Serious Game and close the article with a discussion and conclusions.

The paper is interesting because it highlights an ongoing process in the realm of the visualization of Cultural Heritage (see for example Champion 2016). The process described by the authors on how to accomplish this by using Serious Games, Gamification, Augmented and Virtual Reality is promising, although still hypothetical as the project is ongoing. It remains to be seen if the proposed visuals and interactive elements will work in the way intended and offer users an immersive experience after all. A preliminary questionnaire already showed that most of the respondents were not familiar with these technologies (AR, VR) and in my experience these numbers only change slowly. One way to overcome the technological barrier however might be the gamification of the experience, which the authors are planning to implement.

I decided to recommend this article based on the remarks of the two reviewers, which the authors implemented perfectly, as well as my own evaluation of the paper. Although still in progress it seems worthwhile to have this article as a basis for discussion and comparison to similar projects. However, the article did not mention the possible longevity of data and in which ways the usability of the Serious Game will be secured for long-term storage. One eminent problem in these endeavors is, that we can read about these projects, but never find them anywhere to test them ourselves (see for example Gabellone et al. 2016). It is my intention with this review and the recommendation, that the ECHOES project will find a solution for this problem and that we are not only able to read this (and forthcoming) article(s) about the ECHOES project, but also play the Serious Game they are proposing in the near and distant future.

References

Champion, Erik Malcolm. 2016. „Entertaining the Similarities and Distinctions between Serious Games and Virtual Heritage Projects“. Entertainment Computing 14 (Mai): 67–74. https://doi.org/10.1016/j.entcom.2015.11.003

Gabellone, Francesco, Antonio Lanorte, Nicola Masini, und Rosa Lasaponara. 2016. „From Remote Sensing to a Serious Game: Digital Reconstruction of an Abandoned Medieval Village in Southern Italy“. Journal of Cultural Heritage. https://doi.org/10.1016/j.culher.2016.01.012

Tsaknaki, Electra, Anastasovitis, Eleftherios, Georgiou, Georgia, Alagialoglou, Kleopatra, Mavrokostidou, Maria, Kartsiakli, Vasiliki, Aidonis, Asterios, Protopsalti, Tania, Nikolopoulos, Spiros, and Kompatsiaris, Ioannis. (2023). Designing Stories from the Grave: Reviving the History of a City through Human Remains and Serious Games, Zenodo, 7981323, ver. 4 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7981323

The construction of 3D realities is deeply embedded in archaeological practices. From sites to artifacts, archaeology has dedicated itself to creating digital copies for the most varied purposes. The paper “Visual encoding of a 3D virtual reconstruction's 3 scientific justification: feedback from a proof-of-concept research” (Jean-Yves et al 2024) represents an advance, in the sense that it does not just deal with a three-dimensional theory for archaeological practice, but rather offers proposals regarding the epistemic component, how it is possible to represent knowledge through the workflow of 3D virtual reconstructions themselves. The authors aim to unite three main axes - knowledge modeling, visual encoding and 3D content reuse - (Jean-Yves et al 2024: 2), which, for all intents and purposes, form the basis of this article. With regard to the first aspect, this work questions how it is possible to transmit the knowledge we want to a 3D model and how we can optimize this epistemic component. A methodology based on plausibility criteria is offered, which, for the archaeological field, offers relevant space for reflection. Given our inability to fully understand the object or site that is the subject of the 3D representation, whether in space or time, building a method based on probabilistic categories is probably one of the most realistic approaches to the realities of the past.

Thus, establishing a plausibility criterion allows the user to question the knowledge that is transmitted through the representation, and can corroborate or refute it in future situations. This is because the role of reusing these models is of great interest to the authors, a perfectly justifiable sentiment, as it encourages a critical view of scientific practices. Visual encoding is, in terms of its conjunction with knowledge practices, a key element. The notion of simplicity under Maeda's (2006) design principles not only represents a way of thinking that favors operability, but also a user-friendly design in the prototype that the authors have created. This is also visible when it comes to the reuse of parts of the models, in a chronological logic: adapting the models based on architectural elements that can be removed or molded is a testament to intelligent design, whereby instead of redoing models in their entirety, they are partially used for other purposes.

All these factors come together in the final prototype, a web application that combines relational databases (RDBMS) with a data mapper (MassiveJS), using the PHP programming language.  The example used is the Marmoutier Abbey hostelry, a centuries-old building which, according to the sources presented, has evolved architecturally over several centuries ((Jean-Yves et al 2024: 8). These states of the building are represented visually through architectural elements based on their existence, location, shape and size, always in terms of what is presented as being plausible. This allows not only the creation of a matrix in which various categories are related to various architectural elements, but also a visual aid, through a chromatic spectrum, of the plausibility that the authors are aiming for. 

In short, this is an article that seeks to rethink the degree of knowledge we can obtain through 3D visualizations and that does not take models as static, but rather realities that must be explored, recycled and reinterpreted in the light of different data, users and future research. For this reason, it is a work of great relevance to theoretical advances in 3D modeling adapted to archaeology.

References

Blaise, J.-Y., Dudek, I., Bergerot, L. and Gaël, S. (2024). Visual encoding of a 3D virtual reconstruction's scientific justification: feedback from a proof-of-concept research, Zenodo, 7983163, ver. 3 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.10496540

John Maeda. (2006). The Laws of Simplicity. MIT Press, Cambridge, MA, USA.

This paper presents the use of a participatory arts-based methodology to understand how digital and analogue tools affect individuals' participation in the process of archaeological recording and interpretation. The preliminary results of this work highlight the importance of rethinking archaeologists' relationship with different recording methods, emphasising the need to recognise the value of both approaches and to adopt a documentation strategy that exploits the strengths of both analogue and digital methods.

Although a larger group of participants with broader and more varied experience would have provided a clearer picture of the impact of technology on current archaeological practice, the article makes an important contribution in highlighting the complex and not always easy transition that archaeologists trained in analogue methods are currently experiencing when using digital technology.

 This is assessed by using arts-based methodologies to enable archaeologists to consider how digital technologies are changing the relationship between mind, body and practice.

I found the range of experiences described in the papers by the archaeologists involved in the experiment particularly interesting and very representative of the change in practice that we are all experiencing.  As the article notes, the two approaches cannot be directly compared because they offer different possibilities: if analogue methods foster a deeper connection with the archaeological material, digital documentation seems to be perceived as more effective in terms of data capture, information exchange and data sharing (Araar et al., 2023).

It seems to me that an important element to consider in such a study is the generational shift and the incredible divide between native and non-native digital.

 The critical issues highlighted in the paper are central and provide important directions for navigating this ongoing (digital) transition.

References

Araar, L., Morgan, C. and Fowler, L. (2023) Body Mapping the Digital: Visually representing the impact of technology on archaeological practice., Zenodo, 7990581, ver. 5 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7990581