An Ontology Model for Narrative Image Annotation in the Field of Cultural Heritage

Traditional event models couldn’t model temporal-spatial information very well in narrative image tagging task especially in the field of culture heritage. In this paper, we design a narrative image annotation ontology (NIAO) model and tool (NIA) to address this issue by using ontology design patterns and other related vocabularies for reusability. The annotation model, combining with OAC (Open Annotation Collaboration) framework and regarding Plot as central class, makes a mapping between annotated image regions and high-level image semantics. It has been embedded in NIA which is designed based on html5 and applied in annotation task of narrative paintings successfully. This tool can record annotation region pixels and related property values according to NIAO, and these annotation data can be stored as various formats such as csv, json, and rdf. We have built a SPARQL endpoint, in which end users can make semantic queries based on these annotation data for visualization of the results with pictures rather than tables.