Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Blonde, W; Antezana, E; Mironov, V; Schulz, S; Kuiper, M; De Baets, B.
Using the relation ontology Metarel for modelling Linked Data as multi-digraphs
SEMANT WEB. 2014; 5(2): 115-126.
Doi: 10.3233/SW-130096
Web of Science
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- Führende Autor*innen der Med Uni Graz
- Blondé Ward
- Co-Autor*innen der Med Uni Graz
- Schulz Stefan
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- 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.
- Find related publications in this database (Keywords)
- Linked Data
- RDF
- relations
- Description Logics
- SPARQL
- rules