Topic-Specific Trust and Open Rating Systems: An Approach for Ontology Evaluation

To achieve better interoperability among intelligent applications, and to relieve knowledge engineers from the burden of developing ontologies from scratch, it is critical to reuse ontologies. However, there are two main reasons why the reuse of ontologies is rare: (1) current ontology repositories allow only simple keyword-based search facilities, and (2) even when a user finds an ontology, the information about the ontology quality and (re)usability is not available. In this paper, we present an Open Rating System based approach for ontology evaluation. The core Open Rating System model is extended with topic-specific trust to provide more accurate personalized ontology rankings. Our model is partially implemented in Knowledge Zone—a webbased ontology repository where users can submit their ontologies, annotate them with metadata, search for existing ontologies, find out their rankings based on user reviews, post their own reviews, and rate reviews.