In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domainspecific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects.
Baroncini, S., Sartini, B., Van Erp, M., Tomasi, F., Gangemi, A. (2023). Is dc:subject enough? A landscape on iconography and iconology statements of knowledge graphs in the semantic web. JOURNAL OF DOCUMENTATION, 79(7), 115-136 [10.1108/JD-09-2022-0207].
Is dc:subject enough? A landscape on iconography and iconology statements of knowledge graphs in the semantic web
Baroncini, Sofia;Sartini, Bruno;Tomasi, Francesca;Gangemi, Aldo
2023
Abstract
In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domainspecific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects.File | Dimensione | Formato | |
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