Ontological Access to Images of Fine Art

Information retrieval in a knowledge rich domain poses challenges that are different from other domains. The domain of fine arts and cultural heritage is an exemplar of such a domain. The many facets of, and complex interrelations between, works of fine art are not easily addressed by conventional keyword-based approaches or even by structured cataloguing systems. Information retrieval challenges in this domain include: the conversion of existing legacy data into knowledge representations that emulate the semantics of the domain's relationships; and easy access to a robust knowledge representation for users unfamiliar with query languages. Our research addresses aspects of both challenges as they are connected and may benefit from being addressed in conjunction. Based on a study on user preferences in art image search and a review of existing structured resources for cataloguing art and heritage information, we have developed two prototypes: Ontology Populator and Artfinder. The first prototype, Ontology Populator, is used to automatically enrich data akin to legacy data kept by heritage institutions and transform it into a knowledge base. The second prototype is a graphical query builder, Artfinder, which interacts with the knowledge base. The Artfinder interface, is constructed dynamically from the structure of the underlying knowledge. A task-based evaluation of Artfinder was carried out with 10 expert and 10 layperson evaluators. Participants reviewed the interface favourably and the evaluation also revealed potential for improvement. Artfinder and its "query logic," perhaps is a semantically richer mode of accessing knowledge repositories, allowing for logically more complex queries than are currently supported outside the realm of dedicated query languages. We believe that domain experts and perhaps informed laypersons will benefit from this retrieval approach.