Cancer data integration and querying with genetegra
DILS'12 Proceedings of the 8th international conference on Data Integration in the Life Sciences
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The increasing body of distributed and heterogeneous information and the autonomous, heterogeneous and dynamic nature of information resources are important issues hindering effective and efficient data access, retrieval and knowledge sharing. The importance of ontologies has been recognised within the biomedical domain and work has begun on developing and sharing biomedical ontologies. In this paper, we define ontology and ontology commitments and explain the main characteristics and representations of ontology models. Ontologies are highly expressive knowledge models and as such increase expressiveness and intelligence of a system. We highlight the significance of ontologies in a variety of semi-automatic and automatic tasks, and provide an illustrative example of an ontology-based multi-agent system designed to intelligently retrieve information about human diseases from a number of heterogeneous and dispersed information resources.