Schema Evolution publication categorizer

Ontologies are heavily used in life sciences so that there is increasing value to match different ontologies in order to determine related conceptual categories. We propose a simple yet powerful methodology for instance-based ontology matching which utilizes the associations between molecular-biological objects and ontologies. The approach can build on many existing ontology as-sociations for instance objects like sequences and proteins and thus makes heavy use of available domain knowledge. Furthermore, the approach is flexi-ble and extensible since each instance source with associations to the ontologies of interest can contribute to the ontology mapping. We study several ap-proaches to determine the instance-based similarity of ontology categories. We perform an extensive experimental evaluation to use protein associations for different species to match between subontologies of the Gene Ontology and the OMIM ontology. We also provide a comparison with metadata-based ontology matching.