Cancer data integration and querying with genetegra

Authors:
E. Patrick Shironoshita;Yves R. Jean-Mary;Ray M. Bradley;Patricia Buendia;Mansur R. Kabuka
Affiliations:
INFOTECH Soft, Inc., Miami, FL;INFOTECH Soft, Inc., Miami, FL;INFOTECH Soft, Inc., Miami, FL;INFOTECH Soft, Inc., Miami, FL;INFOTECH Soft, Inc., Miami, FL, USA,University of Miami, Coral Gables, FL
Venue:
DILS'12 Proceedings of the 8th international conference on Data Integration in the Life Sciences
Year:
2012

Citing 10
Cited 0

Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema

ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Anatomy of data integration

Journal of Biomedical Informatics
Ontology Management: Semantic Web, Semantic Web Services, and Business Applications (Semantic Web and Beyond)

Ontology Management: Semantic Web, Semantic Web Services, and Business Applications (Semantic Web and Beyond)
Information integration in the enterprise

Communications of the ACM - Enterprise information integration: and other tools for merging data
Semantic Representation and Querying of caBIG Data Services

DILS '08 Proceedings of the 5th international workshop on Data Integration in the Life Sciences
State of the nation in data integration for bioinformatics

Journal of Biomedical Informatics
Ontology Support for Biomedical Information Resources

CBMS '08 Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems
semQA: SPARQL with Idempotent Disjunction

IEEE Transactions on Knowledge and Data Engineering
Ontology matching with semantic verification

Web Semantics: Science, Services and Agents on the World Wide Web
Reduce, reuse, recycle: practical approaches to schema integration, evolution and versioning

CoMoGIS'06 Proceedings of the 2006 international conference on Advances in Conceptual Modeling: theory and practice

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present the GeneTegra system, an ontology-based information integration environment. We show its ability to query multiple data sources, and we evaluate the relative performance of different data repositories. GeneTegra uses Semantic Web standards to resolve the semantic and syntactic diversity of the large and increasingly complex body of publicly available data. GeneTegra contains mechanisms to create ontology models of data sources using the OWL 2 Web Ontology Language, and to define, plan, and execute queries against these models using the SPARQL query language. Data source formats supported include relational databases and XML and RDF data sources. Experimental results have been obtained to show that GeneTegra obtains equivalent results from different data repositories containing the same data, illustrating the ability of the methods proposed in querying heterogeneous sources using the same modeling paradigm.