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Knowledge representation and ontologies.
Ontologies have become important tools in biomedicine, supporting critical aspects of both health care and biomedical research, including clinical research. Some even see ontologies as integral to science. Unlike terminologies (focusing on naming) and classification systems (developed for partitioning a domain), ontologies define the types of entities that exist, as well as their interrelations. And while knowledge bases generally integrate both definitional and assertional knowledge, ontologies focus on what is always true of entities, i.e., definitional knowledge. In practice, however, there is no sharp distinction between these kinds of artifacts and ‘ontology’ has become a generic name for a variety of knowledge sources with important differences in their degree of formality, coverage, richness and computability. In this chapter, we focus on those ontologies of particular relevance to clinical research. After a brief introduction to ontology development and knowledge representation, we present the characteristics of some of these ontologies. We then show how ontologies are integrated in and made accessible through knowledge repositories, and illustrate their role in clinical research.
Keywords: knowledge representation, biomedical ontologies, research metadata ontology, data content ontology, ontology-driven knowledge bases, data integration, computer reasoning