Ontology Based Indexing Schemes

Infectious disease researchers and clinicians have difficulty in formulating queries that capture the kinds of questions they wish to pose. The taxonomy used to describe micro-biological data is complex; this terminology also changes with time. As a means for overcoming these difficulties, we have developed methods for efficiently integrating semantic knowledge, stored in the form of thesauri (or more precisely, ontologies) in ways that support efficient indexing of large databases. The goal of this effort is to provide clinicians with the ability to express complex queries without becoming experts on the underlying data model. Thus far, we have employed this technique to index relational databases. We will soon adapt this method to support efficient indices for sensor and scientific datasets.

Related Information:	Publication List Project Home Pages In collaboration with the Parallel Understanding Systems (PLUS)research group
Presentations:	Johns Hopkins Pathology Informatics Presentation,  Baltimore, Maryland, July 1998 High Performance Computing in Medicine and Pathology