Determining Semantic Similarity among Entity Classes from Different Ontologies
IEEE Transactions on Knowledge and Data Engineering
Index structures and algorithms for querying distributed RDF repositories
Proceedings of the 13th international conference on World Wide Web
Modeling a description logic vocabulary for cancer research
Journal of Biomedical Informatics
Sharing Data on the Grid using Ontologies and distributed SPARQL Queries
DEXA '07 Proceedings of the 18th International Conference on Database and Expert Systems Applications
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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A computational grid infrastructure for biomedical research, called caGrid, is under development by the National Cancer Institute (NCI) as part of the cancer Biomedical Informatics Grid (caBIG) Initiative. In this paper we present a model that enables users to query an integrated view of caBIG data services at a conceptual semantic level. The model is based on semCDI, a formulation to generate an ontology view of caBIG semantics and pose queries against this view using the SPARQL query language complemented with Horn rules. We present here a mechanism to process these queries algebraically using our semQA query algebra extension for SPARQL, in order to create sub-expressions for each data service. We then show how resulting graphs from these sub-expressions are then merged using Horn rules.