Abstract
Over the past decade, the number, size, and complexity of databases for health-related research have grown dramatically. Ontologies are being developed and used by many scientific communities to support sharing, integration, and management of the diverse information in these databases. As critical as ontologies have become, ontology language such as OWL typically provide minimal support for modeling the complex temporal relationships that are common in biomedical research data. As a result, ontologies often cannot fully express the temporal knowledge needed by many biomedical applications and thus users and developers must pursue ad hoc solutions to these challenges. In this paper, we present a methodology and set of tools for representing temporal information in biomedical ontologies. This approach uses a lightweight temporal model to encode the temporal dimension of biomedical data. It also uses the OWLbased Semantic Web Rule Language (SWRL) and the SWRL-based OWL query language SQWRL to reason with and query the temporal information represented using this model.
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