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Journal of Biomedical Semantics

, 5:46

First Online: 19 November 2014Received: 17 July 2014Accepted: 07 November 2014


BackgroundTwo distinct trends are emerging with respect to how data is shared, collected, and analyzed within the bioinformatics community. First, Linked Data, exposed as SPARQL endpoints, promises to make data easier to collect and integrate by moving towards the harmonization of data syntax, descriptive vocabularies, and identifiers, as well as providing a standardized mechanism for data access. Second, Web Services, often linked together into workflows, normalize data access and create transparent, reproducible scientific methodologies that can, in principle, be re-used and customized to suit new scientific questions. Constructing queries that traverse semantically-rich Linked Data requires substantial expertise, yet traditional RESTful or SOAP Web Services cannot adequately describe the content of a SPARQL endpoint. We propose that content-driven Semantic Web Services can enable facile discovery of Linked Data, independent of their location.

ResultsWe use a well-curated Linked Dataset - OpenLifeData - and utilize its descriptive metadata to automatically configure a series of more than 22,000 Semantic Web Services that expose all of its content via the SADI set of design principles. The OpenLifeData SADI services are discoverable via queries to the SHARE registry and easy to integrate into new or existing bioinformatics workflows and analytical pipelines. We demonstrate the utility of this system through comparison of Web Service-mediated data access with traditional SPARQL, and note that this approach not only simplifies data retrieval, but simultaneously provides protection against resource-intensive queries.

ConclusionsWe show, through a variety of different clients and examples of varying complexity, that data from the myriad OpenLifeData can be recovered without any need for prior-knowledge of the content or structure of the SPARQL endpoints. We also demonstrate that, via clients such as SHARE, the complexity of federated SPARQL queries is dramatically reduced.

KeywordsOpenLifeData Bio2RDF SADI Semantic web services SPARQL SHARE Sentient knowledge explorer Galaxy AbbreviationsDBCLSDatabase center for life science

HTTPHypertext transport protocol

NBDCNational bioscience database center

OPMWOpen provenance model for workflows

OWLWeb ontology language

RDFResource description framework

SPARQLSPARQL Protocol and RDF Query Language

SADISemantic automated discovery and integration


VoIDVocabulary of interlinked datasets.

Electronic supplementary materialThe online version of this article doi:10.1186-2041-1480-5-46 contains supplementary material, which is available to authorized users.

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Author: Alejandro Rodríguez González - Alison Callahan - José Cruz-Toledo - Adrian Garcia - Mikel Egaña Aranguren - Michel Dumo


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