Semantic web data warehousing for caGrid
Identifieur interne : 000209 ( Pmc/Curation ); précédent : 000208; suivant : 000210Semantic web data warehousing for caGrid
Auteurs : James P. Mccusker [États-Unis] ; Joshua A. Phillips [États-Unis] ; Alejandra González Beltrán [Royaume-Uni] ; Anthony Finkelstein [Royaume-Uni] ; Michael Krauthammer [États-Unis]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2009.
Abstract
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.
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DOI: 10.1186/1471-2105-10-S10-S2
PubMed: 19796399
PubMed Central: 2755823
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<front><div type="abstract" xml:lang="en"><p>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<sup>® </sup>
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.</p>
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Department of Pathology, Yale University School of Medicine, New Haven, CT, USA</aff>
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Semantic Bits, LLC, Reston, VA, USA</aff>
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Department of Computer Science, University College London, London, UK</aff>
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<fpage>S2</fpage>
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<permissions><copyright-statement>Copyright © 2009 McCusker et al; licensee BioMed Central Ltd.</copyright-statement>
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<pmc-comment>
McCusker
P
James
james.mccusker@yale.edu
Semantic web data warehousing for caGrid
2009 BMC Bioinformatics 10(Suppl 10): S2-. (2009) 1471-2105(2009)10:Suppl 10 urn:ISSN:1471-2105 </pmc-comment>
</license>
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<abstract><p>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<sup>® </sup>
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.</p>
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