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17 Dec 2020
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Experimentation preceding innovation in a MIS5 Pre-Still Bay layer from Diepkloof Rock Shelter (South Africa): emerging technologies and symbols

Experimentation as a driving force for innovation in the Pre-Still Bay from Southern Africa

Recommended by based on reviews by Francesco d'Errico, Enza Elena Spinapolice and Kathryn Ranhorn

The article submitted by Guillaume Porraz et al. [1] shed light on the evolutionary changes recorded during the Pre-Still Bay Lynn stratigraphic unit (SU) from Diepkloof (Southern Africa). It promotes a multi-proxy and integrative approach based on a set of innovative behaviors, such as the engraving of geometric forms, silcrete heat- treatment, the use of adhesive, bladelet and bifacial tools production. This approach is not so common in Middle Stone Age (MSA) studies and makes a lot of sense for discussing the mechanisms that have fostered later innovations during the Still Bay and Howiesons Poort periods. The various innovations that emerge synchronously in this layer contrast with earlier innovations which appear as isolated phenomena in the MSA archaeological record. The strong inventiveness documented in Lynn SU is reported to a phase of experimentation for testing new ideas, new behaviors that would have played a crucial role for the emergence of the Still Bay in a context of socio-economic transformation.

The data presented in this article broadens the scope of two previous articles [2-3] based on a more representative record, collected on an area of 3,5 m² opposed to 2 m² previously, and on the first presentation and description of an engraved bone with a rhomboid pattern. Macro- and microscopic analyses together with the analysis of the distribution of the engraved lines argue convincingly for an intentional engraving. This article constitutes a key contribution to the question of HOW emerged modern cultures in Southern Africa, while calling for further research related to sites’ function, environment and local resources to address the ever-debated question of WHY the MSA groups from Southern Africa developed such unprecedented inventiveness. It makes no doubt that this article deserves recommendation by PCI Archaeology.

[1] Porraz, G., Schmidt, P., Bereiziat, G., Brugal, J.Ph., Dayet, L., Igreja, M., Miller, C.E., Viola, C., Tribolo, C., Val, A., Verna, C., Texier, P.J. 2020. Experimentation preceding innovation in a MIS5 Pre-Still Bay layer from Diepkloof Rock Shelter (South Africa): emerging technologies and symbols. 10.32942/osf.io/ch53r

[2] Porraz, G., Texier, P.J., Archer, W., Piboule, M., Rigaud, J.P, Tribolo, C. 2013. Technological successions in the Middle Stone Age sequence of Diepkloof Rock Shelter, Western Cape, South Africa. Journal of Archaeological Science 40, 3376–3400. 10.1016/j.jas.2013.02.012

[3] Porraz, G., Texier, J.P. Miller, C.E., 2014. Le complexe bifacial Still Bay et ses modalités d’émergence à l’abri Diepkloof (Middle Stone Age, Afrique du Sud). In: XXVIIème Congrès Préhistorique de France, Transitions, Ruptures et Continuité en Préhistoire. Mémoires de la Société Préhistorique Française, 155–175.

Experimentation preceding innovation in a MIS5 Pre-Still Bay layer from Diepkloof Rock Shelter (South Africa): emerging technologies and symbolsGuillaume Porraz, John E. Parkington, Patrick Schmidt, Gérald Bereiziat, Jean-Philip Brugal, Laure Dayet, Marina Igreja, Christopher E. Miller, Viola C. Schmid, Chantal Tribolo, Aurore Val, Christine Verna, Pierre-Jean Texier<p>In South Africa, key technologies and symbolic behaviors develop as early as the later Middle Stone Age in MIS5. These innovations arise independently in various places, contexts and forms, until their full expression during the Still Bay and t...Africa, Lithic technology, Middle Palaeolithic, Symbolic behavioursAnne Delagnes2020-08-04 09:13:27 View
14 May 2024
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Supporting the analysis of a large coin hoard with AI-based methods

A demonstration of the use and finetuning of existing machine learning tools for analysing large complexes of coins

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

The paper outlines the ClaReNet project's exploration of computer-based methods for classifying Celtic coin series, specifically focusing on a hoard from Jersey [1]. They collaborated with Jersey Heritage and numismatists, utilising a large dataset of coin images. The process involves stages such as pre-sorting, size-based sorting, class/type identification, and die studies. They employed IT methods, including object detection and unsupervised learning, followed by supervised learning for data refinement. Collaboration with numismatic experts ensured data quality. The study highlighted challenges in classifying coins, suggesting techniques like image matching alongside convolutional neural networks (CNNs). The results demonstrate the efficacy of semi-automatic processes in coin classification, emphasising the importance of human-computer collaboration for successful outcomes.

Overall, this is a good paper, showing how we as archaeologists and numismatics can use existing tools and finetune them for our purposes; without the need for huge domain specific datasets. This research and related papers show how we can more effectively deal with the increasingly bigger data we deal with, saving time on the monotonous and labour intensive tasks, leaving us more time to deal with the big picture. An important strength of the work is the provided public software repository and the dataset. The paper is well written, and a number of images illustrate the methodology as well as the objects used.

Reference

[1] Deligio, C., Tolle, K., and Wigg-Wolf, D. (2024). Supporting the analysis of a large coin hoard with AI-based methods. Zenodo, 8301464, ver. 4 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.8301464

 

 

Supporting the analysis of a large coin hoard with AI-based methodsChrisowalandis Deligio, Karsten Tolle, David Wigg-Wolf<p>In the project "Classifications and Representations for Networks: From types and characteristics to linked open data for Celtic coinages" (ClaReNet) we had access to image data for one of the largest Celtic coin hoards ever found: Le Câtillon I...Computational archaeologyAlex Brandsen2023-08-30 15:31:16 View
21 Mar 2023
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Archaeology, Typology and Machine Epistemology

Automation and Novelty –Archaeocomputational Typo-Praxis in the Wake of the Third Science Revolution

Recommended by ORCID_LOGO, and ORCID_LOGO based on reviews by Rachel Crellin and 1 anonymous reviewer

“Archaeology, Typology and Machine Epistemology” submitted by G. Lucas (1) offers a refreshing and welcome reflection on the role of computer-based practice, type-thinking and approaches to typology in the age of big data and the widely proclaimed ‘Third Science Revolution’ (2–4). At the annual meeting of the EAA in Maastricht in 2017, a special thematic block was dedicated to issues and opportunities linked to the Third Science Revolution in archaeology “because of [its] profound and wide ranging impact on practice and theory in archaeology for the years to come” (5). Even though the Third Science Revolution, as influentially outlined by Kristiansen in 2014 (2), has occasionally also been met with skepticism and critique as to its often implicit scientism and epistemological naivety (6–8), archaeology as a whole seems largely euphoric as to the promises of the advancing ‘revolution’. As Lucas perceptively points out, some even regard it as the long-awaited opportunity to finally fulfil the ambitions and goals of Anglophone processualism. The irony here, as Lucas rightly notes, is that early processualists initially foregrounded issues of theory and scientific epistemology, while much work conducted under the banner of the Third Science Revolution, especially within its computational branches, does not. Big data advocates have echoed Anderson’s much-cited “end of theory” (9) or at least emphatically called for an ‘empirization’ and ‘computationalization’ of theory, often under the banner of ‘data-driven archaeology’ (10), yet typically without much specification of what this is supposed to mean for archaeological theory and reflexivity. The latter is indeed often openly opposed by archaeological Third Science Revolution enthusiasts, arguably because it is viewed as part of the supposedly misguided ‘post-modernist’ project.

Lucas makes an original meta-archaeological contribution here and attempts to center the epistemological, ontological and praxeological dimensions of what is actually – in situated archaeological praxis and knowledge-production – put at stake by the mobilization of computers, algorithms and artificial intelligence (AI), including its many but presently under-reflected implications for ordering practices such as typologization. Importantly, his perspective thereby explicitly and deliberately breaks with the ‘normative project’ in traditional philosophy of science, which sought to nail down a universal, prescriptive way of doing science and securing scientific knowledge. He instead focuses on the practical dimensions and consequences of computer-reliant archaeologies, what actually happens on the ground as researchers try to grapple with the digital and the artefactual and try to negotiate new insights and knowledge, including all of the involved messiness – thereby taking up the powerful impetus of the broader practice turn in interdisciplinary science studies and STS (Science and Technology Studies (11)) (12–14), which have recently also re-oriented archaeological self-observation, metatheory and epistemology (15). This perspective on the dawning big data age in archaeology and incurred changes in the status, nature and aims of type-thinking produces a number of important insights, which Lucas fruitfully discusses in relation to promises of ‘automation’ and ‘novelty’ as these feature centrally in the rhetorics and politics of the Third Science Revolution. 

With regard to automation, Lucas makes the important point that machine or computer work as championed by big data proponents cannot adequately be qualified or understood if we approach the issue from a purely time-saving perspective. The question we have to ask instead is what work do machines actually do and how do they change the dynamics of archaeological knowledge production in the process? In this optic, automation and acceleration achieved through computation appear to make most sense in the realm of the uncontroversial, in terms of “reproducing an accepted way of doing things” as Lucas says, and this is precisely what can be observed in archaeological practice as well. The ramifications of this at first sight innocent realization are far-reaching, however. If we accept the noncontroversial claim that automation partially bypasses the need for specialists through the reproduction of already “pre-determined outputs”, automated typologization would primarily be useful in dealing with and synthesizing larger amounts of information by sorting artefacts into already accepted types rather than create novel types or typologies. If we identity the big data promise at least in part with automation, even the detection of novel patterns in any archaeological dataset used to construct new types cannot escape the fact that this novelty is always already prefigured in the data structure devised. The success of ‘supervised learning’ in AI-based approaches illustrates this. Automation thus simply shifts the epistemological burden back to data selection and preparation but this is rarely realized, precisely because of the tacit requirement of broad non-contentiousness. 

Minimally, therefore, big data approaches ironically curtail their potential for novelty by adhering to conventional data treatment and input formats, rarely problematizing the issue of data construction and the contested status of (observational) data themselves. By contrast, they seek to shield themselves against such attempts and tend to retain a tacit universalism as to the nature of archaeological data. Only in this way is it possible to claim that such data have the capacity to “speak for themselves”. To use a concept borrowed from complexity theory, archaeological automation-based type-construction that relies on supposedly basal, incontrovertible data inputs can only ever hope to achieve ‘weak emergence’ (16) – ‘strong emergence’ and therefore true, radical novelty require substantial re-thinking of archaeological data and how to construct them. This is not merely a technical question as sometimes argued by computational archaeologies – for example with reference to specifically developed, automated object tracing procedures – as even such procedures cannot escape the fundamental question of typology: which kind of observations to draw on in order to explore what aspects of artefactual variability (and why). The focus on readily measurable features – classically dimensions of artefactual form – principally evades the key problem of typology and ironically also reduces the complexity of artefactual realities these approaches assert to take seriously. The rise of computational approaches to typology therefore reintroduces the problem of universalism and, as it currently stands, reduces the complexity of observational data potentially relevant for type-construction in order to enable to exploration of the complexity of pattern. It has often been noted that this larger configuration promotes ‘data fetishism’ and because of this alienates practitioners from the archaeological record itself – to speak with Marxist theory that Lucas briefly touches upon. We will briefly return to the notion of ‘distance’ below because it can be described as a symptomatic research-logical trope (and even a goal) in this context of inquiry. 

In total, then, the aspiration for novelty is ultimately difficult to uphold if computational archaeologies refuse to engage in fundamental epistemological and reflexive self-engagement. As Lucas poignantly observes, the most promising locus for novelty is currently probably not to be found in the capacity of the machines or algorithms themselves, but in the modes of collaboration that become possible with archaeological practitioners and specialists (and possibly diverse other groups of knowledge stakeholders). In other words, computers, supercomputers and AI technologies do not revolutionize our knowledge because of their superior computational and pattern-detection capacities – or because of some mysterious ‘superintelligence’ – but because of the specific ‘division of labour’ they afford and the cognitive challenge(s) they pose. Working with computers and AI also often requires to ask new questions or at least to adapt the questions we ask. This can already be seen on the ground, when we pay attention to how machine epistemologies are effectively harnessed in archaeological practice (and is somewhat ironic given that the promise of computational archaeology is often identified with its potential to finally resolve "long-standing (old) questions"). The Third Science Revolution likely prompts a consequential transformation in the structural and material conditions of the kinds of ‘distributed’ processes of knowledge production that STS have documented as characteristic for scientific discoveries and knowledge negotiations more generally (14, 17, 18). This ongoing transformation is thus expected not only to promote new specializations with regard to the utilization of the respective computing infrastructures emerging within big data ecologies but equally to provoke increasing demand for new ways of conceptualizing observations and to reformulate the theoretical needs and goals of typology in archaeology. The rediscovery of reflexivity as an epistemic virtue within big data debates would be an important step into this direction, as it would support the shared goal of achieving true epistemic novelty, which, as Lucas points out, is usually not more than an elusive self-declaration. Big data infrastructures require novel modes of human-machine synergy, which simply cannot be developed or cultivated in an atheoretical and/or epistemological disinterested space. 

Lucas’ exploration ultimately prompts us to ask big questions (again), and this is why this is an important contribution. The elephant in the room, of course, is the overly strong notion of objectivity on which much computational archaeology is arguably premised – linked to the vow to eventually construct ‘objective typologies’. This proclivity, however, re-tables all the problematic debates of the 1960s and – to speak with the powerful root metaphor of the machine fueling much of causal-mechanistic science (19, 20) – is bound to what A. Wylie (21) and others have called the ‘view from nowhere’. Objectivity, in this latter view, is defined by the absence of positionality and subjectivity – chiefly human subjectivity – and the promise of the machine, and by extension of computational archaeology, is to purify and thus to enhance processes of knowledge production by minimizing human interference as much as possible. The distancing of the human from actual processes of data processing and inference is viewed as positive and sometimes even as an explicit goal of scientific development. Interestingly, alienation from the archaeological record is framed as an epistemic virtue here, not as a burden, because close connection with (or even worse, immersion in) the intricacies of artefacts and archaeological contexts supposedly aggravates the problem of bias. The machine, in this optic, is framed as the gatekeeper to an observer-independent reality – which to the backdoor often not only re-introduces Platonian/Aristotelian pledges to a quasi-eternal fabric of reality that only needs to be “discovered” by applying the right (broadly nonhuman) means, it is also largely inconsistent with defendable and currently debated conceptions of scientific objectivity that do not fall prey to dogma.  

Furthermore, current discussions on the open AI ChatGPT have exposed the enormous and still under-reflected dangers of leaning into radical renderings of machine epistemology: precisely because of the principles of automation and the irreducible theory-ladenness of all data, ecologies such as ChatGPT tend to reinforce the tacit epistemological background structures on which they operate and in this way can become collaborators in the legitimization and justification of the status quo (which again counteracts the potential for novelty) – they reproduce supposedly established patterns of thought. This is why, among other things, machines and AI can quickly become perpetuators of parochial and neocolonial projects – their supposed authority creates a sense of impartiality that shields against any possible critique. With Lucas, we can thus perhaps cautiously say that what is required in computational archaeology is to defuse the authority of the machine in favour of a new community archaeology that includes machines as (fallible) co-workers. Radically put, computers and AI should be recognized as subjects themselves, and treated as such, with interesting perspectives on team science and collaborative practice.

 

Bibliography

1. Lucas, G. (2022). Archaeology, Typology and Machine Epistemology. https:/doi.org/10.5281/zenodo.7620824.

2. Kristiansen, K. (2014). Towards a New Paradigm? The Third Science Revolution and its Possible Consequences in Archaeology. Current Swedish Archaeology 22, 11–34. https://doi.org/10.37718/CSA.2014.01.

3. Kristiansen, K. (2022). Archaeology and the Genetic Revolution in European Prehistory. Elements in the Archaeology of Europe. https://doi.org/10.1017/9781009228701

4. Eisenhower, M. S. (1964). The Third Scientific Revolution. Science News 85, 322/332. https://www.sciencenews.org/archive/third-scientific-revolution.

5. The ‘Third Science Revolution’ in Archaeology. http://www.eaa2017maastricht.nl/theme4 (March 16, 2023).

6. Ribeiro, A. (2019). Science, Data, and Case-Studies under the Third Science Revolution: Some Theoretical Considerations. Current Swedish Archaeology 27, 115–132. https://doi.org/10.37718/CSA.2019.06

7. Samida, S. (2019). “Archaeology in times of scientific omnipresence” in Archaeology, History and Biosciences: Interdisciplinary Perspectives, pp. 9–22. https://doi.org/10.1515/9783110616651

8. Sørensen, T. F.. (2017). The Two Cultures and a World Apart: Archaeology and Science at a New Crossroads. Norwegian Archaeological Review 50, 101–115. https://doi.org/10.1080/00293652.2017.1367031

9. Anderson, C. (2008). The end of theory: The data deluge makes the scientific method obsolete. Wired. https://www.wired.com/2008/06/pb-theory/.

10. Gattiglia, G. (2015). Think big about data: Archaeology and the Big Data challenge. Archäologische Informationen 38, 113–124. https://doi.org/10.11588/ai.2015.1.26155

11. Hackett, E. J. (2008). The handbook of science and technology studies, Third edition, MIT Press/Society for the Social Studies of Science.

12. Ankeny, R., Chang, H., Boumans, M. and Boon, M. (2011). Introduction: philosophy of science in practice. Euro Jnl Phil Sci 1, 303. https://doi.org/10.1007/s13194-011-0036-4

13. Soler, L., Zwart, S., Lynch, M., Israel-Jost, V. (2014). Science after the Practice Turn in the Philosophy, History, and Social Studies of Science, Routledge.

14. Latour, B. and Woolgar, S. (1986). Laboratory life: the construction of scientific facts, Princeton University Press.

15. Chapman, R. and Wylie, A. (2016) Evidential reasoning in archaeology, Bloomsbury Academic.

16. Greve, J. and Schnabel, A. (2011). Emergenz: zur Analyse und Erklärung komplexer Strukturen, Suhrkamp.

17. Shapin, S., Schaffer, S. and Hobbes, T. (1985). Leviathan and the air-pump: Hobbes, Boyle, and the experimental life, including a translation of Thomas Hobbes, Dialogus physicus de natura aeris by Simon Schaffer, Princeton University Press.

18. Galison, P. L. and Stump, D. J. (1996).The Disunity of Science: Boundaries, Contexts, and Power, Stanford University Press.

19. Pepper, S. C. (1972). World hypotheses: a study in evidence, 7. print, University of California Press.

20. Hussain, S. T. (2019). The French-Anglophone divide in lithic research: A plea for pluralism in Palaeolithic Archaeology, Open Access Leiden Dissertations. https://hdl.handle.net/1887/69812 

21. A. Wylie, A. (2015). “A plurality of pluralisms: Collaborative practice in archaeology” in Objectivity in Science, pp. 189-210, Springer. https://doi.org/10.1007/978-3-319-14349-1_10

Archaeology, Typology and Machine EpistemologyGavin Lucas<p>In this paper, I will explore some of the implications of machine learning for archaeological method and theory. Against a back-drop of the rise of Big Data and the Third Science Revolution, what lessons can be drawn from the use of new digital...Computational archaeology, Theoretical archaeologyShumon Tobias HussainAnonymous, Rachel Crellin2022-10-31 15:25:38 View
23 Nov 2023
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Percolation Package - From script sharing to package publication

Sharing Research Code in Archaeology

Recommended by ORCID_LOGO based on reviews by Thomas Rose, Joe Roe and 1 anonymous reviewer

​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

Percolation Package - From script sharing to package publicationSophie C Schmidt; Simon Maddison<p>In this paper we trace the development of an R-package starting with the adaptation of code from a different field, via scripts shared between colleagues, to a published package that is being successfully used by researchers world-wide. Our aim...Computational archaeologyJames Allison2023-05-24 15:40:15 View
28 Feb 2021
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A database of lapidary artifacts in the Caribbean for the Ceramic Age

Open data on beads, pendants, blanks from the Ceramic Age Caribbean

Recommended by ORCID_LOGO based on reviews by Clarissa Belardelli, Stefano Costa, Robert Bischoff and Li-Ying Wang

The paper 'A database of lapidary artifacts in the Caribbean for the Ceramic Age' by Queffelec et al. [1] presents a description of a dataset of nearly 5000 lapidary artefacts from over 100 sites. The data are dominated by beads and pendants, which are mostly made from Diorite, Turquoise, Carnelian, Amethyst, and Serpentine. The raw material data is especially valuable as many of these are not locally available on the island. This holds great potential for exchange network analysis. The data may be especially useful for investigating one of the fundamental questions of this region: whether the Cedrosan and Huecan are separate, little related developments, with different origins, or variants or a single tradition [2].

In addition to metric and technological details about the artefacts, the data include a variety of locational details, including coordinates, distance to coast, and altitude. This enables many opportunities for future spatial analysis and geostatistical modelling to understand human behaviours relating to ornament production, use, and discard. I recommend the authors make a minor revision to Table 1 (spatial coverage of the dataset) to make the column with the citations conform to the same citation style used in the rest of the text.

I warmly commend the authors for making transparency and reproducibility a priority when preparing their manuscript. Their use of the R Markdown format for writing reproducible, dynamic documents [3] is highly impressive. This is an excellent example for others in the international archaeological science community to follow. The paper is especially useful for researchers who are new to R and R Markdown because of the elegant and accessible way the authors document their research here.

[1] Queffelec, A., Fouéré, P. and Caverne, J.-B. 2021. A database of lapidary artifacts in the Caribbean for the Ceramic Age. SocArXiv, 7dq3b, ver. 4 Peer-reviewed and recommended by PCI Archaeology. https://doi.org/10.31235/osf.io/7dq3b

[2] Reed, J. A. and Petersen, J. B. 2001. A comparison of Huecan and Cedrosan Saladoid ceramics at the Trants site, Montserrat. In Proceedings of the XVIIIth International Congress for Caribbean Archaeology (pp. 253-267).

[3] Marwick, B. 2017. Computational Reproducibility in Archaeological Research: Basic Principles and a Case Study of Their Implementation. Journal of Archaeological Method and Theory 24, 424–450. https://doi.org/10.1007/s10816-015-9272-9

A database of lapidary artifacts in the Caribbean for the Ceramic AgeAlain Queffelec, Pierrick Fouéré, Jean-Baptiste Caverne<p>Lapidary artifacts show an impressive abundance and diversity during the Ceramic period in the Caribbean islands, especially at the beginning of this period. Most of the raw materials used in this production do not exist naturally on the island...Neolithic, North America, Raw materials, South America, Spatial analysis, Symbolic behavioursBen Marwick2020-11-13 23:52:34 View
10 Jan 2024
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Linking Scars: Topology-based Scar Detection and Graph Modeling of Paleolithic Artifacts in 3D

A valuable contribution to automated analysis of palaeolithic artefacts

Recommended by ORCID_LOGO based on reviews by Lutz Schubert and 1 anonymous reviewer

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

Linking Scars: Topology-based Scar Detection and Graph Modeling of Paleolithic Artifacts in 3DFlorian Linsel, Jan Philipp Bullenkamp & Hubert Mara<p>Motivated by the concept of combining the archaeological practice of creating lithic artifact drawings with the potential of 3D mesh data, our goal in this project is not only to analyze the shape at the artifact level, but also to enable a mor...Computational archaeology, Europe, Lithic technology, Upper PalaeolithicSebastian Hageneuer2023-09-01 23:03:59 View
20 Jul 2022
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Faunal remains from the Upper Paleolithic site of Nahal Rahaf 2 in the southern Judean Desert, Israel

New zooarchaeological data from the Upper Palaeolithic site of Nahal Rahaf 2, Israel

Recommended by ORCID_LOGO based on reviews by Ana Belén Galán and Joana Gabucio

The Levantine Corridor is considered a crossing point to Eurasia and one of the main areas for detecting population flows (and their associated cultural and economic changes) during the Pleistocene. This area could have been closed during the most arid periods, giving rise to processes of population isolation between Africa and Eurasia and intermittent contact between Eurasian human communities [1,2]. 

Zooarchaeological studies of the early Upper Palaeolithic assemblages constitute an important source of knowledge about human subsistence, making them central to the debate on modern behaviour. The Early Upper Palaeolithic sequence in the Levant includes two cultural entities – the Early Ahmarian and the Levantine Aurignacian. This latter is dated to 39-33 ka and is considered a local adaptation of the European Aurignacian techno-complex. In this work, the authors present a zooarchaeological study of the Nahal Rahaf 2 (ca. 35 ka) archaeological site in the southern Judean Desert in Israel [3].

Zooarchaeological data from the early Upper Paleolithic desert regions of the southern Levant are not common due to preservation problems of non-lithic finds. In the case of Nahal Rahaf 2, recent excavation seasons brought to light a stratigraphical sequence composed of very well-preserved archaeological surfaces attributed to the 'Arkov-Divshon' cultural entity, which is associated with the Levantine Aurignacian. 

This study shows age-specific caprine (Capra cf. Capra ibex) hunting on prime adults and a generalized procurement of gazelles (Gazella cf. Gazella gazella), which seem to have been selectively transported to the site and processed for within-bone nutrients. An interesting point to note is that the proportion of goats increases along the stratigraphic sequence, which suggests to the authors a specialization in the economy over time that is inversely related to the occupational intensity of use of the site. 

It is also noteworthy that the materials represent a large sample compared to previous studies from the Upper Paleolithic of the Judean Desert and Negev.

In summary, this manuscript contributes significantly to the study of both the palaeoenvironment and human subsistence strategies in the Upper Palaeolithic and provides another important reference point for evaluating human hunting adaptations in the arid regions of the southern Levant.

References

[1] Bermúdez de Castro, J.-L., Martinon-Torres, M. (2013). A new model for the evolution of the human pleistocene populations of Europe. Quaternary Int. 295, 102-112. https://doi.org/10.1016/j.quaint.2012.02.036

[2] Bar-Yosef, O., Belfer-Cohen, A. (2010). The Levantine Upper Palaeolithic and Epipalaeolithic. In Garcea, E.A.A. (Ed), South-Eastern Mediterranean Peoples Between 130,000 and 10,000 Years Ago. Oxbow Books, pp. 144-167.

[3] Marom, N., Gnezdilov, D. L., Shafir, R., Barzilai, O. and Shemer, M. (2022). Faunal remains from the Upper Paleolithic site of Nahal Rahaf 2 in the southern Judean Desert, Israel. BioRxiv, 2022.05.17.492258, ver. 4 peer-reviewed and recommended by Peer community in Archaeology. https://www.biorxiv.org/content/10.1101/2022.05.17.492258v4

Faunal remains from the Upper Paleolithic site of Nahal Rahaf 2 in the southern Judean Desert, IsraelNimrod Marom, Dariya Lokshin Gnezdilov, Roee Shafir, Omry Barzilai, Maayan Shemer<p>Nahal Rahaf 2 (NR2) is an Early Upper Paleolithic (ca. 35 kya) rock shelter in the southern Judean Desert in Israel. Two excavation seasons in 2019 and 2020 revealed a stratigraphical sequence composed of intact archaeological surfaces attribut...Upper Palaeolithic, ZooarchaeologyRuth Blasco Joana Gabucio2022-05-19 06:16:47 View
29 Jan 2024
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Visual encoding of a 3D virtual reconstruction's scientific justification: feedback from a proof-of-concept research

3D Models, Knowledge and Visualization: a prototype for 3D virtual models according to plausible criteria

Recommended by based on reviews by Robert Bischoff and Louise Tharandt

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.

Visual encoding of a 3D virtual reconstruction's scientific justification: feedback from a proof-of-concept researchJ.Y Blaise, I.Dudek, L.Bergerot, G.Simon<p>&nbsp;3D virtual reconstructions have become over the last decades a classical mean to communicate &nbsp;about analysts’ visions concerning past stages of development of an edifice or a site. However, they still today remain quite often a one-s...Computational archaeology, Spatial analysisDaniel Carvalho2023-05-30 00:43:03 View
02 Sep 2023
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Towards a Mobile 3D Documentation Solution. Video Based Photogrammetry and iPhone 12 Pro as Fieldwork Documentation Tools

The Potential of Mobile 3D Documentation using Video Based Photogrammetry and iPhone 12 Pro

Recommended by based on reviews by Dominik Hagmann, Sebastian Hageneuer and 1 anonymous reviewer

I am pleased to recommend the paper titled "Towards a Mobile 3D Documentation Solution. Video Based Photogrammetry and iPhone 12 Pro as Fieldwork Documentation Tools" for consideration and publication as a preprint (Paukkonen, 2023). The paper addresses a timely and relevant topic within the field of archaeology and offers valuable insights into the evolving landscape of 3D documentation methods.

The advances in technology over the past decade have brought about significant changes in archaeological documentation practices. This paper makes a valuable contribution by discussing the emergence of affordable equipment suitable for 3D fieldwork documentation. Given the constraints that many archaeologists face with limited resources and tight timeframes, the comparison between photogrammetry based on a video captured by a DJI Osmo Pocket gimbal camera and iPhone 12 Pro LiDAR scans is of great significance.

The research presented in the paper showcases a practical application of these new technologies in the context of a Finnish Early Modern period archaeological project. By comparing the acquisition processes and evaluating the accuracy, precision, ease of use, and time constraints associated with each method, the authors provide a comprehensive assessment of their potential for archaeological fieldwork. This practical approach is a commendable aspect of the paper, as it not only explores the technical aspects but also considers the practical implications for archaeologists on the ground.

Furthermore, the paper appropriately addresses the limitations of these technologies, specifically highlighting their potential inadequacy for projects requiring a higher level of precision, such as Neolithic period excavations. This nuanced perspective adds depth to the discussion and provides a realistic portrayal of the strengths and limitations of the new documentation methods.

In conclusion, the paper offers valuable insights into the future of 3D field documentation for archaeologists. The authors' thorough evaluation and practical approach make this study a valuable resource for researchers, practitioners, and professionals in the field. I believe that this paper would be an excellent addition to PCIArchaeology and would contribute significantly to the ongoing dialogue within the archaeological community.

References

Paukkonen, N. (2023) Towards a Mobile 3D Documentation Solution. Video Based Photogrammetry and iPhone 12 Pro as Fieldwork Documentation Tools, Zenodo, 8281263, ver. 3 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.8281263

Towards a Mobile 3D Documentation Solution. Video Based Photogrammetry and iPhone 12 Pro as Fieldwork Documentation ToolsNikolai Paukkonen<p>New affordable equipment suitable for 3D fieldwork documentation has appeared during the last years. Both photogrammetry and laser scanning are becoming affordable for archaeologists, who often work with limited resources and tight time constra...Europe, Post-medieval, Remote sensingYing Tung Fung2023-05-21 21:32:33 View
31 Jan 2024
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Rivers vs. Roads? A route network model of transport infrastructure in Northern Italy during the Roman period

Modelling Roman Transport Infrastructure in Northern Italy

Recommended by based on reviews by Pau de Soto and Adam Pažout

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

Rivers vs. Roads? A route network model of transport infrastructure in Northern Italy during the Roman periodJames Page<p>Northern Italy has often been characterised as an isolated and marginal area during the Roman period, a region constricted by mountain ranges and its distance from major shipping lanes. Historians have frequently cited these obstacles, alongsid...Classic, Computational archaeologyAndrew McLean2023-05-28 15:11:31 View