Abstract
BackgroundSemantic Web has established itself as a framework for using and sharing data across applications and database boundaries. Here, we present a web-based platform for querying biological Semantic Web databases in a graphical way.ResultsSPARQLGraph offers an intuitive drag & drop query builder, which converts the visual graph into a query and executes it on a public endpoint. The tool integrates several publicly available Semantic Web databases, including the databases of the just recently released EBI RDF platform. Furthermore, it provides several predefined template queries for answering biological questions. Users can easily create and save new query graphs, which can also be shared with other researchers.ConclusionsThis new graphical way of creating queries for biological Semantic Web databases considerably facilitates usability as it removes the requirement of knowing specific query languages and database structures. The system is freely available at http://sparqlgraph.i-med.ac.at.
Highlights
Semantic Web has established itself as a framework for using and sharing data across applications and database boundaries
SPARQLGraph SPARQLGraph is a web-based platform allowing users to build Semantic Web database queries in a novel, graphical way
The main interface of the platform consists of a large drawing board that is used to assemble new query graphs
Summary
Semantic Web has established itself as a framework for using and sharing data across applications and database boundaries. We present a web-based platform for querying biological Semantic Web databases in a graphical way. The vast majority of this data is accessible through heterogeneous relational databases and traditional keyword searching. Effective research in life sciences is thereby currently hampered by the absence of integrated databases, and will get even more difficult as more and more biological data accumulates. Over the last few years, the Semantic Web has established itself as a common framework allowing data to be used and shared across applications and database boundaries. Several biological Semantic Web databases and services for querying and integrating heterogeneous biological databases have emerged, trying to bring the advantages of Semantic Web to the life sciences community [1]. EBI very recently launched its own Semantic Web platform [3] for several of its databases, including UniProt, ChEMBL, and Reactome
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