PCI Archaeology

397

Title *

Supporting the analysis of a large coin hoard with AI-based methodsuse asterix (*) to get italics

Authors *

Chrisowalandis Deligio, Karsten Tolle, David Wigg-WolfPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

Year *

2024

Picture *

Abstract *

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 II with nearly 70,000 coins. Our aim was not to develop new processes, but rather to demonstrate how existing tools can be used to support the numismatic task of processing and analysing large complexes of coins, thus validating the enormous potential of IT-based methods. The main steps involved are the pre-sorting of coins by size (denomination), the attribution of individual coins to classes or types, and finally the identification of which coins were struck by individual dies.  The process from digitisation of a hoard as images to an actual die study is lengthy and work-intensive. In testing methods to support each of the steps, we focussed  particularly on methods that do not need any prior knowledge of the material, in order  to explore whether these methods can be applied to a dataset for which there is no more information than the images themselves. The different steps were evaluated against information provided by the numismatist working on the hoard (class and die attributions of the coins), who was also involved in different stages of the process.  The result is a workflow that can be used in future work on large coin finds, thus supporting numismatists and significantly speeding up the work of identification and analysis.  This paper also presents tools, visualisation methods and extensions that proved useful, both for the individual processes, as well as for communicating with the numismatists and integrating their expertise. Earlier phases of our work were presented at CAA 2022 in Oxford.

Indicate the full web address (DOI or URL) giving public access to these data (if you have any problems with the deposit of your data, please contact contact@archaeo.peercommunityin.org). In case all raw data are included in the preprint, indicate the DOI or URL of the preprint. *

https://catalogue.jerseyheritage.org/categories/celtic-coin-hoard/You should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://

Indicate the full web address (DOI or URL) giving public access to these scripts (if you have any problems with the deposit of your scripts, please contact contact@archaeo.peercommunityin.org). In case all raw scripts are included in the preprint, indicate the DOI or URL of the preprint. *

https://doi.org/10.5281/zenodo.8301158You should fill this box only if you chose 'Scripts were used to obtain or analyze the results'. URL must start with http:// or https://

Indicate the full web address (DOI, SWHID or URL) giving public access to these codes (if you have any problems with the deposit of your codes, please contact contact@archaeo.peercommunityin.org). In case all raw codes are included in the preprint, indicate the DOI or URL of the preprint. *

https://doi.org/10.5281/zenodo.8301158You should fill this box only if you chose 'Codes have been used in this study'. URL must start with http:// or https://

Keywords (optional)

machine learning, celtic coins, classification, unsupervised learning, object detection

Methods that require specific expertise (optional)

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Thematic fields *

Computational archaeology

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Submission date

2023-08-30 15:31:16

Recommender

Alex Brandsen

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