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

In the task of tagging narrative images, traditional event or story models are not suitable for temporal-spatial information modeling. These models are too coarse-grained to represent plots and actions information sufficiently in the particular field of culture heritage. In this paper, we design a narrative image annotation ontology (NIAO) model and a tool (NIA) to address these issues, by using ontology design patterns and other relevant models for reusability. The annotation model, combining the OAC (Open Annotation Collaboration) framework and regarding the Plot as a core element, makes a mapping between annotated image regions and high-level image semantics. It has been embedded in NIA, which we successfully use in the task of annotating narrative paintings. 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, and visualize the results with pictures rather than tables