Review Comment:
The paper is clear and well-written. It deals with an important topic, i.e. the integration of data resulting from scientific analyses with other archaeological documentation. Overall, the argumentation is clear and well explained.
That said, I have however some comments including a general one, which in my opinion deserve authors’ attention. If authors wish, it may require a major revision of the paper.
I am a bit uncomfortable in quoting my own research or work done by research teams in which I am directly involved. Please note that I am not looking for more quotations: my comments below are only aimed at improving an already very good paper as the present one, and at avoiding criticism once it is published. Authors should feel free to decide if and how they wish to take my suggestions into account.
In the introduction, authors list a number of initiatives that make archaeological datasets “increasingly available online” and list some very important ones. But, in this survey, they ignore the aggregating function of the ARIADNEplus project, which they mention only as regards a study on the archaeological users’ needs, a side topic of the ARIADNE research.
Actually, ARIADNEplus makes about 1.7 million archaeological datasets findable, accessible (within the limits of the original access license), interoperable and retrievable, using a CIDOC CRM compliant ontology. The original data are stored with institutions from all Europe (not only ADS) and can be retrieved via the ARIADNE catalogue at portal.ariadne-infrastructure.eu. The outcomes of ARIADNE until 2019 and its follow-up ARIADNEplus have been published in an edited volume “The ARIADNE Impact”. A more technical description of the (first) ARIADNE project has appeared on JOCCH, see below. Item-level integration with archaeological science is work in progress, so very few reports about archaeological sciences are included in the catalogue – and, in general, are available online.
A humorous aspect of the above forgetfulness is that the institution to which one of the authors belongs, INFN CHNet, is an active ARIADNE partner and is currently developing the extension of the CRM ontology to archaeological scientific data and promoting their inclusion in the catalogue: gnothi seauton, Know Thyself, would say Socrates.
In conclusion, not mentioning the ARIADNE contribution may derive from deliberate disregard or from distraction: the former is fine but should be explained; the latter is not appropriate in a scientific paper for a project which has thousands of users.
However, a major issue, in my opinion, is the lack of consideration about what is called “data provenance”. This term usually indicates the circumstances of data acquisition and processing, producing so-called raw (numeric) data and any further transformation of them. All digital instrumentation processes analog measurements internally to convert the analog measurements into numbers, the raw data. The pipeline from physical or chemical results to digital raw data is relevant to assess the reliability of the latter. This pipeline often includes “black boxes”, for example proprietary devices or software included (and not disclosed to users) in the processing. The environmental conditions under which the experiment is made, its operational protocol, and even the research question for which it was carried out originally are all relevant for the reliability of the results. For example, stating that an XRF analysis showed that a pigment is Egyptian blue means nothing if it is not stated which XRF device was used, if a cheap handheld one or a laboratory-grade one. The instrument settings and calibration are also important. Since authors mention, among others, photogrammetry and 2D/3D acquisition (page 12), documenting the environmental conditions of the data acquisition is of paramount importance. In this case, also the goal of the original investigation matters, as it may influence the chosen precision, the detail level and so on. I add below some relevant references for the digital provenance issue.
As a matter of fact, all this information is usually recorded in the archaeometry report: this includes statements such as “we analyzed a sample taken from X, with the device Y and settings Z following protocol W”: but all this disappears when collapsed into S21 Measurement. Thus, potential re-users of the archaeometry analyses remain puzzled if the data are suitable and reliable enough, or not, for their research.
Sometimes this is the consequence of a dismissive attitude (“I’m the scientist and don’t bother me”). For sure this is not the case with this paper, so show that it isn’t.
I assume – perhaps a bit overoptimistically – that authors are aware of these considerations and would like to mention the above-mentioned issue as forthcoming work, improving and detailing their ontology. This is by no means mandatory for publication. They should consider my comments as a friendly warning towards possible criticism to their paper and suggestions to improve the in-depth semantic integration of all contributions to archaeological research, of which archaeometry is in my opinion a key one, and their work a valid contribution.
Thus, I will not object to publication is such comments are disregarded. The decision, and responsibility, is up to authors.
Here are some references (for reading, not necessarily for quoting!).
About ARIADNE/ARIADNEplus
C. Meghini et al (2017J “ARIADNE: A Research Infrastructure for Archaeology”, Journal on Computing and Cultural Heritage, Volume 10, Issue 3 - August 2017, Article No.: 18, pp 1–27. https://doi.org/10.1145/3064527
J. Richards and F. Niccolucci (eds.) (2019) The ARIADNE Impact Archaeolingua, Budapest.
https://zenodo.org/badge/DOI/10.5281/zenodo.4319058.svg
About data provenance (mainly about digital provenance)
M. Doerr and M. Theodoridou (2011) “CRMdig: A Generic Digital Provenance Model for Scientific Observation” 3rd {USENIX} Workshop on the Theory and Practice of Provenance (TaPP 11). Available at https://www.usenix.org/conference/tapp11/crmdig-generic-digital-provenan...
N. Amico, P. Ronzino, A. Felicetti, F. Niccolucci (2013) “Quality management of 3D cultural heritage replicas with CIDOC-CRM” Proceedings of CRMEX@ TPDL http://ceur-ws.org/Vol-1117/
K. Tzompanaki, M. Doerr, M. Theodoridou, I. Fundulaki (2014) “Reasoning based on property propagation on CIDOC-CRM and CRMdig based repositories” available here: https://www.semanticscholar.org/paper/Reasoning-based-on-property-propag...
C. Strubulis, G. Flouris, Y. Tzitzikas, and M- Doerr (2014) “A case study on propagating and updating provenance information using the CIDOC CRM” International J. on Digital Libraries 15, 27–51. Doi: 10.1007/s00799-014-0125-z
N- Carboni et al. (2016 ) “Data provenance in photogrammetry through documentation protocols” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume III-5, 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic, 57-64. Available at https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-5/5...
Ontology extension to heritage science
F. Niccolucci and A. Felicetti (2018) "A CIDOC CRM-based Model for the Documentation of Heritage Sciences," 2018 3rd Digital Heritage International Congress (DigitalHERITAGE) held jointly with 2018 24th International Conference on Virtual Systems & Multimedia (VSMM 2018), San Francisco, USA, pp. 1-6, doi: 10.1109/DigitalHeritage.2018.8810109
L. Castelli, A. Felicetti and F. Proietti F. (2019) “Heritage Science and Cultural Heritage: standards and tools for establishing cross-domain data interoperability” International J. on Digital Libraries, doi: 10.1007/s00799-019-00275-2
Other papers are forthcoming from this INFN-based team
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