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

The paper “A closer look at an eroded dune landscape: first functional insights into the Federmessergruppen site of Lommel-Maatheide” [1] focuses on the final Palaeolithic (Federmesser) site of Lommel-Maatheide. Federmesser sites from northern Belgium such as Lommel-Maatheide, Meer and Rekem, show evidence for dense human occupation of specific areas located on top of Tardiglacial dunes nearby water bodies [2]. Preserved spatial distribution of finds at the sites suggest different activity areas and the presence of habitat structures [2]. However, because of the low organic preservation at the sites, functional analyses of lithic assemblages have the potential to significantly contribute to the spatial organisation of activities at these sites. This study by Tomasso et al. [1], represents an excellent example of a large-scale integrated approach to the study of lithic industries. The article undoubtedly demonstrates the potential of the proposed methodology and the reliability of the results obtained.

The article explores two different aspects (linked and excellently interconnected here): the possibility to apply use wear, residue and fracture analyses, on lithic assemblages affected by taphonomical alterations and to study lithic assemblages from dune landscapes. 

The study allows to answer differentiated questions: what is the influence of taphonomical alterations on use wear analysis? How do excavation methods impact the formation of use wear and the preservation of residues? Can we recognize distinct domestic activities? The article also provides an interesting hypothesis about hunting activities and propulsion methods.

The applied methodology is effectively interdisciplinary and innovative. It demonstrates how a truly integrated and articulated approach can represent the turning point for going beyond a mainly descriptive dimension to move towards a real understanding of the sites.

Studies dedicated to the analysis of the propulsion mode are not very frequent, but they are surely very important to better understand human behaviour [3]. Here, the methodology developed for the evaluation of the propulsion mode represent an important starting point for the definition of a new approach. Morphological and morphometrical analysis are integrated to the evaluation of the mechanical stress, to fracture delineations and to the hafting system (the latter defined on experimental basis).

This article therefore underlines the potential of combining different approaches to functional analysis associated with a ‘tailored’ reference collection and applying them to a high number of artefacts for reconstructing past human activities involving materials that are otherwise not preserved in these contexts. 

[1] Tomasso, S., Cnuts, D., Coppe, J., Geerts, F., Gils, M.V., Bie, M.D., Rots, V. (2021). A closer look at an eroded dune landscape: first functional insights into the Federmessergruppen site of Lommel-Maatheide. https://doi.org/10.31219/osf.io/pf3sm, ver 3 peer-reviewed and recommended by PCI Archaeology.

[2] De Bie, M., Van Gils, M. (2006). Les habitats des groupes à Federmesser (aziliens) dans le Nord de la Belgique. Bulletin de la Société préhistorique française, 103, 781–790.

[3] Coppe, J., Lepers, C., Clarenne, V., Delaunois, E., Pirlot, M. and Rots V. (2019). Ballistic Study Tackles Kinetic Energy Values of Palaeolithic Weaponry. Archaeometry, (61)4, 933-956. https://doi.org/10.1111/arcm.12452

“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

The paper by Plutniak [1] presents a new method that uses refitting to help interpret stratigraphy using the topological distribution of conjoinable material culture. This new method opens up new avenues to the archaeological use of network analysis but also to assess the integrity of interpreted excavation layers. Beyond its evident applicability to standard excavation practice, the paper presents a series of characteristics that exemplify archaeological publication best practices and, as someone more versed in computational than in refitting studies I would like to comment upon.

It was no easy task to find adequate reviewers for this paper as it combines techniques and expertise that are not commonly found together in individual researchers. However, Plutniak, with help from three reviewers, particularly M. Peeples, a leading figure in archaeological applications of network science, makes a considerable effort to be accessible to non-specialist archaeologists. The core Topological Study of Archaeological Refitting (TSAR) method is freely accessible as the R package archeofrag, which is available at the Comprehensive R Archive Network (https://CRAN.R-project.org/package=archeofrag) that can be applied without the need to understand all its mathematical, graph theory and coding aspects. Beside these, an online interface including test data has been provided (https://analytics.huma-num.fr/Sebastien.Plutniak/archeofrag/), which aims to ease access to the method to those archaeologists inexperienced with R. Finally, supplementary material showing how to use the package and evaluating its potential through excellent examples is provided as both pdf and Rmw (Sweave) files. This is an important companion for the paper as it allows a better understanding of the methods presented in the paper and its practical application.

The author shows particular care in testing the potential and capabilities of the method. For example, a function is provided “frag.observer.failure” to test the robustness of the edge count method against the TSAR method, which is able to prove that TSAR can deal well with incomplete information. As a further step in this direction both simulated and real field-acquired data are used to test the method which further proves that archeofrag is not only able to quantitatively assess the mixture of excavated layers but to propose meaningful alternatives, which no doubt will add an increased methodological consistency and thoroughness to previous quantitative approaches to material refitting work, even when dealing with very complex stratigraphies.

All in all, this paper makes an important contribution to core archaeological practice through the use of innovative, reproducible and accessible computational methods. I fully endorse it for the conscious and solid methods it presents but also for its adherence to open publication practices. I hope that it can become of standard use in the reconstruction of excavated stratigraphical layers through conjoinable material culture.

[1] Plutniak, S. 2021. The Strength of Parthood Ties. Modelling Spatial Units and Fragmented Objects with the TSAR Method – Topological Study of Archaeological Refitting. OSF Preprints, q2e69, ver. 3 Peer-reviewed and recommended by PCI Archaeology. https://doi.org/10.31219/osf.io/q2e69.

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.