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semCDI: A Query Formulation for Semantic Data Integration in caBIG

^a INFOTECH Soft, Inc., Miami, FL
^b University of Miami, Coral Gables, FL.

^_* Correspondence and reprints: Dr. Mansur R. Kabuka, INFOTECH Soft, Inc., 9200 Dadeland Blvd., Ste 620, Miami, FL 33156 (Email: kabuka{at}infotechsoft.com).

Received for publication: 01/28/08; accepted for publication: 04/16/08.

Objectives: To develop mechanisms to formulate queries over the semantic representation of cancer-related data services available through the cancer Biomedical Informatics Grid (caBIG).

Design: The semCDI query formulation uses a view of caBIG semantic concepts, metadata, and data as an ontology, and defines a methodology to specify queries using the SPARQL query language, extended with Horn rules. semCDI enables the joining of data that represent different concepts through associations modeled as object properties, and the merging of data representing the same concept in different sources through Common Data Elements (CDE) modeled as datatype properties, using Horn rules to specify additional semantics indicating conditions for merging data.

Validation: In order to validate this formulation, a prototype has been constructed, and two queries have been executed against currently available caBIG data services.

Discussion: The semCDI query formulation uses the rich semantic metadata available in caBIG to build queries and integrate data from multiple sources. Its promise will be further enhanced as more data services are registered in caBIG, and as more linkages can be achieved between the knowledge contained within caBIG's NCI Thesaurus and the data contained in the Data Services.

Conclusion: semCDI provides a formulation for the creation of queries on the semantic representation of caBIG. This constitutes the foundation to build a semantic data integration system for more efficient and effective querying and exploratory searching of cancer-related data.