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Knowledge Graph based Analysis and Exploration of Historical Theatre Photographs


Knowledge Graph based Analysis and Exploration of Historical Theatre Photographs



Published: 2020
Herausgeber: CEUR
Buchtitel: Proceedings of the Conference on Digital Curation Technologies (Qurator 2020)
Ausgabe: 2535
Verlag: CEUR
Organisation: Conference on Digital Curation Technologies (Qurator 2020)

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BibTeX

Kurzfassung
Historical theatre collections are an important form of cul- tural heritage and need to be preserved and made accessible to users. Often however, the metadata available for a historical collection are too sparse to create meaningful exploration tools. On the use case of a histor- ical theatre photograph collection, this position paper discusses means of automated recognition of historical images to enhance the variety and depth of the metadata associated to the collection. Moreover, it describes how the results obtained by image recognition can be integrated into an existing Knowledge Graph (KG) and how these generated structured im- age metadata can support data exploration and automated querying to support human users. The goal of the paper is to explore cultural her- itage data curation techniques based on deep learning and KGs to make the data findable, accessible, interoperable and reusable in accordance with the F.A.I.R principles.

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Forschungsgruppe

Information Service Engineering


Forschungsgebiet