Semantic web data warehousing for caGrid.
The National Cancer Institute (NCI) is developing caGrid as a means for sharing cancer-related data and services. As more data sets become available on caGrid, we need effective ways of accessing and integrating this information. Although the data models exposed on caGrid are semantically well annotated, it is currently up to the caGrid client to infer relationships between the different models and their classes. In this paper, we present a Semantic Web-based data warehouse (Corvus) for creating relationships among caGrid models. This is accomplished through the transformation of semantically-annotated caBIG Unified Modeling Language (UML) information models into Web Ontology Language (OWL) ontologies that preserve those semantics. We demonstrate the validity of the approach by Semantic Extraction, Transformation and Loading (SETL) of data from two caGrid data sources, caTissue and caArray, as well as alignment and query of those sources in Corvus. We argue that semantic integration is necessary for integration of data from distributed web services and that Corvus is a useful way of accomplishing this. Our approach is generalizable and of broad utility to researchers facing similar integration challenges.
Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
Jamie P
JP
McCusker
Joshua A
JA
Phillips
Alejandra
A
González Beltrán
Anthony
A
Finkelstein
Michael
M
Krauthammer
D014408:Biomarkers, Tumor / Q000737:chemistry; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D009363:Neoplasm Proteins / Q000737:chemistry; D009369:Neoplasms / Q000378:metabolism*; D012660:Semantics; D014584:User-Computer Interface
D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins