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

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

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

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

References

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

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

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

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

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

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

Silica coating developed in cave art walls had an impact in the preservation of the paintings themselves. Despite it still exists a controversy about whether or not the effects contribute to the preservation of the artworks; it is evident that identifying these silica coatings would have an impact to assess the taphonomy of the walls and the paintings preserved on them. Unfortunately, current techniques -especially non-invasive ones- can hardly address amorphous silica characterisation. Thus, its presence is often detected on laboratory observations such as SEM or XRD analyses. In the paper “Light in the Cave: Opal coating detection by UV-light illumination and fluorescence in a rock art context - Methodological development and application in Points Cave (Gard, France)”, Quiers and collaborators propose a new method for the in situ detection and characterisation of amorphous silica in a rock art context based on UV laser-induced fluorescence (LIF) and UV illumination [1].

The results from both methods presented by the authors are convincing for the detection of U-silica mineralisation (U-opal in the specific case of study presented). This would allow access to a fast and cheap method to identify this kind of formations in situ in decorated caves. Beyond the relationship between opal coating and the preservation of the rock art, the detection of silica mineralisation can have further implications. First, it can help to define spot for sampling for pigment compositions, as well as reconstruct the chronology of the natural history of the caves and its relation with the human frequentation and activities. In conclusion, I am glad to recommend this original research, which offers a new approach to the identification of geological processes that affect -and can be linked with- the Palaeolithic cave art.

[1] Quiers, M., Chanteraud, C., Maris-Froelich, A., Chalmin-Aljanabi, E., Jaillet, S., Noûs, C., Pairis, S., Perrette, Y., Salomon, H., Monney, J. (2022) Light in the Cave: Opal coating detection by UV-light illumination and fluorescence in a rock art context. Methodological development and application in Points Cave (Gard, France). HAL, hal-03383193, ver. 5 peer-reviewed and recommended by Peer community in Archaeology. https://hal.archives-ouvertes.fr/hal-03383193v5

In this paper [1], the authors describe how they apply machine learning with YOLOv5 to classify visual data, aiming to enhance understanding of archaeological phenomena before conducting destructive fieldwork. Despite challenges, the integration of machine learning with remote sensing technology was seen as transformative, enabling precise recording of areas of interest and assessment of environmental risk factors. The paper discusses successes, failures, and future directions in machine learning research, emphasising the need for standardisation and integration of streamlined methods. The application of machine learning techniques facilitates non-destructive analysis of material culture records, improving conservation efforts and offering insights into both past and contemporary phenomena. While the initial use of YOLOv5 showed potential for consistent detection of archaeological features, further refinement and dataset enlargement are deemed necessary for broader application in non-destructive archaeological surveying. The authors advocate for the integration of machine learning tools in archaeological research to save time, resources, and promote ethical digital recording practices. They highlight the importance of standardised methodologies to enhance credibility and reproducibility, aiming to contribute to the ongoing dialogue in computational archaeology.

Overall, I think this paper is a good step forward in detecting small objects in UAV data, and contains useful information for similar studies. The aim towards greater reproducibility and standardisation is of course shared more widely in the machine learning community, and this study is a good example of how to approach this.

References

[1] Sharp, K., Christofis, B., Eslamiat, H., Nepal, U. and Osores Mendives, C. (2024). Machine Learning for UAV and Ground-Captured Imagery: Toward Standard Practices. Zenodo, 8307612, ver. 5 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.8307612

The advent of biomolecular methods has certainly increased our overall comprehension of archaeological societies. One of the materials of choice to perform ancient DNA or proteomics analyses is dental calculus[1,2], a mineralised biofilm formed during the life of one individual. Research conducted in the past few decades has demonstrated the potential of dental calculus to retrieve information about past societies health[3–6], diet[7–11], and more recently, as a putative proxy for isotopic analyses[12]. 

Based on a proof-of-concept previously published by their team[13], Bartholdy and collaborators’ paper presents the identification of compounds and their secondary metabolites derived from consumed plants in individuals from a XIXth century rural Dutch archaeological deposit[14]. Sørensen indeed demonstrated that drug intake is recorded in dental calculus, which are mineralised biofilms that can encapsulate drug compounds long after the latter are no longer detectable in blood. The liquid-chromatography coupled to mass spectrometry (LC-MS/MS)-based method developed showed the potential for archaeological applications[13]. 

Bartholdy et al. utilised the developed LC-MS/MS method to 41 buried individuals, most of them bearing pipe notches on their teeth, from the cemetery of the 19th rural settlement of Middenbeemster, the Netherlands. Along with dental calculus sampling and analysis, they undertook the skeletal and dental examination of all of the specimens in order to assess sex, age-at-death, and pathology on the two tissues. The results obtained on the dental calculus of the sampled individuals show probable consumption of tea, coffee and tobacco indicated by the detection of the various plant compounds and associated metabolites (caffeine, nicotine and salicylic acid, amongst others). 

The authors were able to place their results in perspective and propose several interpretations concerning the ingestion of plant-derived products, their survival in dental calculus and the importance of their findings for our overall comprehension of health and habits of the XIXth c. Dutch population. The paper is well-written and accessible to a non-specialist audience, maximising the impact of their study. I personally really enjoyed handling this manuscript that is not only a good piece of scientific literature but also a pleasant read, the reason why I warmly recommend this paper to be accessible through PCI Archaeology.

References

1.      Fagernäs, Z. and Warinner, C. (2023) Dental Calculus. in Handbook of Archaeological Sciences 575–590. https://doi.org/10.1002/9781119592112.ch28

2.      Wright, S. L., Dobney, K. & Weyrich, L. S. (2021) Advancing and refining archaeological dental calculus research using multiomic frameworks. STAR: Science & Technology of Archaeological Research 7, 13–30. https://doi.org/10.1080/20548923.2021.1882122

3.      Fotakis, A. K. et al. (2020) Multi-omic detection of Mycobacterium leprae in archaeological human dental calculus. Philos. Trans. R. Soc. Lond. B Biol. Sci. 375, 20190584. https://doi.org/10.1098/rstb.2019.0584

4.      Warinner, C. et al. (2014) Pathogens and host immunity in the ancient human oral cavity. Nat. Genet. 46, 336–344. https://doi.org/10.1038/ng.2906

5.      Weyrich, L. S. et al. (2017) Neanderthal behaviour, diet, and disease inferred from ancient DNA in dental calculus. Nature 544, 357–361. https://doi.org/10.1038/nature21674

6.      Jersie-Christensen, R. R. et al. (2018) Quantitative metaproteomics of medieval dental calculus reveals individual oral health status. Nat. Commun. 9, 4744. https://doi.org/10.1038/s41467-018-07148-3

7.      Hendy, J. et al. (2018) Proteomic evidence of dietary sources in ancient dental calculus. Proc. Biol. Sci. 285. https://doi.org/10.1098/rspb.2018.0977

8.      Wilkin, S. et al. (2020) Dairy pastoralism sustained eastern Eurasian steppe populations for 5,000 years. Nat Ecol Evol 4, 346–355. https://doi.org/10.1038/s41559-020-1120-y

9.      Bleasdale, M. et al. (2021) Ancient proteins provide evidence of dairy consumption in eastern Africa. Nat. Commun. 12, 632. https://doi.org/10.1038/s41467-020-20682-3

10.   Warinner, C. et al. (2014) Direct evidence of milk consumption from ancient human dental calculus. Sci. Rep. 4, 7104. https://doi.org/10.1038/srep07104

11.   Buckley, S., Usai, D., Jakob, T., Radini, A. and Hardy, K. (2014) Dental Calculus Reveals Unique Insights into Food Items, Cooking and Plant Processing in Prehistoric Central Sudan. PLoS One 9, e100808. https://doi.org/10.1371/journal.pone.0100808

12.   Salazar-García, D. C., Warinner, C., Eerkens, J. W. and Henry, A. G. (2023) The Potential of Dental Calculus as a Novel Source of Biological Isotopic Data. in Exploring Human Behavior Through Isotope Analysis: Applications in Archaeological Research (eds. Beasley, M. M. & Somerville, A. D.) 125–152. https://doi.org/10.1007/978-3-031-32268-6_6

13.   Sørensen, L. K., Hasselstrøm, J. B., Larsen, L. S. and Bindslev, D. A. (2021) Entrapment of drugs in dental calculus - Detection validation based on test results from post-mortem investigations. Forensic Sci. Int. 319, 110647. https://doi.org/10.1016/j.forsciint.2020.110647

14.   Bartholdy, Bjørn Peare, Hasselstrøm, Jørgen B., Sørensen, Lambert K., Casna, Maia, Hoogland, Menno, Historisch Genootschap Beemster and Henry, Amanda G. (2023) Multiproxy analysis exploring patterns of diet and disease in dental calculus and skeletal remains from a 19th century Dutch population, Zenodo, 7649150, ver. 5 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7649150

Data authenticity and approaches to data authentication are crucial issues in ancient protein research. The advent of modern mass spectrometry has enabled the detection of traces of ancient biomolecules contained in fossils, including protein sequences. However, detecting proteins in ancient samples does not equate to demonstrating their endogenous nature: instead, if the mechanisms that drive protein preservation and degradation are understood, then the extent of protein diagenesis can be used for evaluating preservational quality, which in turn may be related to the authenticity of the protein data. 

The post-mortem deamidation of asparaginyl and glutamyl residues is a key degradation reaction, which can be assessed effectively on the basis of mass spectrometry data, and which has accrued a long history of research, both in terms of describing the mechanisms governing the reactions and with regard to the best strategies for assessing and quantifying the extent of glutamine (Gln) and asparagine (Asn) deamidation in ancient samples (Pal Chowdhury et al., 2019; Ramsøe et al., 2021, 2020; Schroeter and Cleland, 2016; Simpson et al., 2016; Solazzo et al., 2014; Welker et al., 2016; Wilson et al., 2012). 

In their paper, Nair and colleagues (2022) build on this wealth of knowledge and present a tool for quantifying the extent of Gln deamidation in parchment. Parchment is a collagen-based material which can yield extraordinary insights into manuscript manufacturing practices in the past, as well as on the daily lives of the people who assembled and used them (“biocodicology”) (Fiddyment et al., 2021, 2019, 2015; Teasdale et al., 2017). Importantly, the extent of deamidation can be directly related to the quality of the parchment produced: rapid direct deamidation of Gln is induced by the liming process, therefore high extents of deamidation are linked to prolonged exposure to the high pH conditions which are typical of liming, thus implying lower-quality parchment.

Nair et al.’s approach focuses on collagen peptides which are typically detected during MALDI-TOF mass spectrometry analyses of parchment and build a simple three-step workflow able to yield an overall index of deamidation for a sample (the parchment glutamine index - PQI) 一 taking into account that different Gln residues degrade at different rates according to their micro-chemical environment. The first step involves pre-processing the MALDI spectra, since Nair et al. are specifically interested in maximising information which can be obtained by low-quality data. The second step builds on well-established methods for quantifying Q → E from MALDI-TOF data by modelling the convoluted isotope distributions (Wilson et al., 2012). Once relative rates of deamidation in selected peptides within a given sample are calculated, the third step uses a mixed effects model to combine the individual deamidation estimates and to obtain an overall estimate of the deamidation for a parchment sample (PQI). 

The PQI can be used effectively for assessing parchment quality, as the authors show for the dataset from Orval Abbey. However, PQI could also have wider applications to the study of processed collagen, which is widely used in the food and pharmaceutical industries. In general, the study by Nair et al. is a welcome addition to a growing body of research on protein diagenesis, which will ultimately improve models for the assessment of the authenticity of biomolecular data in archaeology. 

References

Chowdhury, P.M., Wogelius, R., Manning, P.L., Metz, L., Slimak, L., and Buckley, M. 2019. Collagen deamidation in archaeological bone as an assessment for relative decay rates. Archaeometry 61:1382–1398. https://doi.org/10.1111/arcm.12492

Fiddyment, S., Goodison, N.J., Brenner, E., Signorello, S., Price, K., and Collins, M.J.. 2021. Girding the loins? Direct evidence of the use of a medieval parchment birthing girdle from biomolecular analysis. bioRxiv. https://doi.org/10.1098/rsos.202055

Fiddyment,S., Holsinger, B., Ruzzier, C., Devine, A., Binois, A., Albarella, U., Fischer, R., Nichols, E., Curtis, A., Cheese, E., Teasdale, M.D., Checkley-Scott, C., Milner, S.J., Rudy, K.M., Johnson, E.J., Vnouček, J., Garrison, M., McGrory, S., Bradley, D.G., and Collins, M.J. 2015. Animal origin of 13th-century uterine vellum revealed using noninvasive peptide fingerprinting. Proc Natl Acad Sci U S A 112:15066–15071. https://doi.org/10.1073/pnas.1512264112

Fiddyment, S., Teasdale, M.D., Vnouček, J., Lévêque, É., Binois, A., and Collins, M.J. 2019. So you want to do biocodicology? A field guide to the biological analysis of parchment. Heritage Science 7:35. https://doi.org/10.1186/s40494-019-0278-6

Nair, B., Rodríguez Palomo, I., Markussen, B., Wiuf, C., Fiddyment, S., and Collins, M. Parchment Glutamine Index (PQI): A novel method to estimate glutamine deamidation levels in parchment collagen obtained from low-quality MALDI-TOF data. BiorRxiv, 2022.03.13.483627, ver. 6 peer-reviewed and recommended by Peer community in Archaeology. https://doi.org/10.1101/2022.03.13.483627 

Ramsøe, A., Crispin, M., Mackie, M., McGrath, K., Fischer, R., Demarchi, B., Collins, M.J., Hendy, J., and Speller, C. 2021. Assessing the degradation of ancient milk proteins through site-specific deamidation patterns. Sci Rep 11:7795. https://doi.org/10.1038/s41598-021-87125-x

Ramsøe, A., van Heekeren, V., Ponce, P., Fischer, R., Barnes, I., Speller, C., and Collins, M.J. 2020. DeamiDATE 1.0: Site-specific deamidation as a tool to assess authenticity of members of ancient proteomes. J Archaeol Sci 115:105080. https://doi.org/10.1016/j.jas.2020.105080

Schroeter, E.R., and Cleland, T.P. 2016. Glutamine deamidation: an indicator of antiquity, or preservational quality? Rapid Commun Mass Spectrom 30:251–255. https://doi.org/10.1002/rcm.7445

Simpson, J.P., Penkman, K.E.H., and Demarchi, B. 2016. The effects of demineralisation and sampling point variability on the measurement of glutamine deamidation in type I collagen extracted from bone. J Archaeol Sci 69: 29-38. https://doi.org/10.1016/j.jas.2016.02.002

Solazzo, C., Wilson, J., Dyer, J.M., Clerens, S., Plowman, J.E., von Holstein, I., Walton Rogers, P., Peacock, E.E., and Collins, M.J. 2014. Modeling deamidation in sheep α-keratin peptides and application to archeological wool textiles. Anal Chem 86:567–575. https://doi.org/10.1021/ac4026362

Teasdale, M.D., Fiddyment, S., Vnouček, J., Mattiangeli, V., Speller, C., Binois, A., Carver, M., Dand, C., Newfield, T.P., Webb, C.C., Bradley, D.G., and Collins M.J. 2017. The York Gospels: a 1000-year biological palimpsest. R Soc Open Sci 4:170988. https://doi.org/10.1098/rsos.170988

Welker, F., Soressi, M.A., Roussel, M., van Riemsdijk, I., Hublin, J.-J., and Collins, M.J. 2016. Variations in glutamine deamidation for a Châtelperronian bone assemblage as measured by peptide mass fingerprinting of collagen. STAR: Science & Technology of Archaeological Research 3:15–27. https://doi.org/10.1080/20548923.2016.1258825

Wilson, J., van Doorn, N.L., and Collins, M.J. 2012. Assessing the extent of bone degradation using glutamine deamidation in collagen. Anal Chem 84:9041–9048. https://doi.org/10.1021/ac301333t