Evidence map›Paper›PMID 23586394›Full record

ArticleBMC bioinformatics2013

Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases.

Julien Wollbrett, Pierre Larmande, Frédéric de Lamotte, Manuel Ruiz

Abstract read
In one paragraph

Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Julien WollbrettCIRAD, UMR AGAP, Montpellier F-34398, France. julien.wollbrett@cirad.fr
Pierre Larmande
Frédéric de Lamotte
Manuel Ruiz

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn 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.

resultsWe 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: (i) the generation and semi-automatic annotation of an RDF view; and (ii) 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.

conclusionsBioSemantic 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 http://southgreen.cirad.fr/?q=content/Biosemantic.

Indexed as

Databases, GeneticSoftwareAlgorithmsGenome, PlantInternetOryzaSemanticsSystems IntegrationVocabulary, Controlled

Identifiers

PMID23586394
PMCPMC3680174

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.