Affiliations: Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure links 653, 9000 Gent, Belgium. E-mail: {ward.blonde,bernard.debaets}@ugent.be | Department of Biology, Norwegian University of Science and Technology, Realfagbygget DU1-111, Høgskoleringen 5, Trondheim, Norway. E-mail: {erick.antezana,vladimir.mironov,martin.kuiper}@bio.ntnu.no | Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2, 8036 Graz, Austria. E-mail: {ward.blonde,stefan.schulz}@medunigraz.at | University Medical Center, Freiburg, Germany
Note: [] Corresponding author.
Abstract: The Semantic Web standards OWL and RDF are often used to represent biomedical information as Linked Data; however, the OWL/RDF syntax, which combines both, was never optimised for querying. By combining two formal paradigms for modelling Linked Data, namely multi-digraphs and Description Logic, many precise terms for relations have emerged that are defined in the Metarel relation ontology. They are especially useful in Linked Data and RDF knowledge bases that 1) rely on SPARQL querying and 2) require semantic support for chains of relations. Metarel-described multi-digraphs were used for knowledge integration and reasoning in three RDF knowledge bases in the domain of genome biology: BioGateway, Cell Cycle Ontology and Gene Expression Knowledge Base. These knowledge bases integrate both data, like KEGG, and ontologies, like Gene Ontology, in the same RDF graphs. Their libraries with biomedically relevant SPARQL queries show the practical benefits of this semantic paradigm. In addition to the management of RDF stores, this paper describes how Metarel can be used for remodelling Linked Data as SPARQL-friendly and semantically rich multi-digraphs. Metarel can be downloaded from http://www.semantic-systems-biology.org/metarel.
