Authors:
Martin J. O’Connor
and
Amar K. Das
Affiliation:
Stanford University, United States
Keyword(s):
Temporal models, Temporal reasoning, Temporal queries, Semantic Web, SWRL, SQWRL, OWL.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Design and Development Methodologies for Healthcare IT
;
Enterprise Information Systems
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Medical and Nursing Informatics
;
Ontologies and the Semantic Web
;
Semantic Interoperability
;
Society, e-Business and e-Government
;
Web Information Systems and Technologies
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 OWL-based 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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