Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases
Identifieur interne : 000405 ( Ncbi/Checkpoint ); précédent : 000404; suivant : 000406Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases
Auteurs : Julien Wollbrett [France] ; Pierre Larmande [France] ; Frédéric De Lamotte [France] ; Manuel Ruiz [France]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2013.
Abstract
In recent years, a large amount of “-omics” data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers.
We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts:
BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at
Url:
DOI: 10.1186/1471-2105-14-126
PubMed: 23586394
PubMed Central: 3680174
Affiliations:
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PMC:3680174Le document en format XML
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>In recent years, a large amount of “-omics” data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers.</p>
</sec>
<sec><title>Results</title>
<p>We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: <italic>(i)</italic>
the generation and semi-automatic annotation of an RDF view; and <italic>(ii)</italic>
the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases.</p>
</sec>
<sec><title>Conclusions</title>
<p>BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at <ext-link ext-link-type="uri" xlink:href="http://southgreen.cirad.fr/?q=content/Biosemantic">http://southgreen.cirad.fr/?q=content/Biosemantic</ext-link>
.</p>
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