Diving into artworks interpretations through the lenses of semantic data: an application on Panofsky's iconological studies

Iconology and Iconography are branches of art history that focus on recognizing and interpreting the subject matter represented in visual artworks and the deeper meanings possibly conveyed. Due to its complex and interpretative nature, iconographical and iconological knowledge is usually recorded in catalog entries in free text fields, making information retrieval challenging. However, having such curated data described with the accuracy and flexibility offered by ontologies would allow us not only to explore the art history scholarly discourse through quantitative analysis but also to enable a new way to access cultural heritage objects described in the network of Linked Open Data (LOD) through the narratives of experts' interpretations. The current doctoral thesis aimed to fill this gap by presenting 1) an ontology for describing iconographical and iconological interpretations, 2) an RDF dataset including a selection of iconographical and iconological interpretations by the art historian Erwin Panofsky, chosen as a case study, and 3) a quantitative analysis to verify whether data-driven iconological inquiries can be valuable for the domain. The resulting Iconology dataset, described through the newly created ICON ontology, covers core aspects of the domain according to three levels of interpretation and provides every subject recognition with provenance information. Although limited to the interests of the art historian, results show that the availability of such curated, authoritative data, described with a high level of granularity, allows us to quantitatively address traditional art historical questions on several topics and conduct new historiographical inquiries on the art historian's method. Furthermore, the implementation of exploratory data analysis on an online interactive dashboard shows the potential of domain-specific information retrieval. This contribution opens up the possibility to link artworks at their content level, allowing content-based research questions in art history to cross into the linked open data realm.