Title :
mOntage: Building Domain Ontologies from Linked Open Data
Author :
Dastgheib, Shima ; Mesbah, Ali ; Kochut, Krys
Author_Institution :
Dept. of Comput. Sci., Univ. of Georgia, Athens, GA, USA
Abstract :
Domain-specific ontologies have become integral components of numerous semantic- and knowledge-based applications. However, creating such ontologies and populating them with correct individuals is a difficult and time-consuming process. Recently, a vast amount of knowledge has become available as part of the Linking Open Data (LOD) project. In this paper, we introduce mOntage, an ontology design and population framework, which allows a domain expert to quickly define a domain ontology schema and then automatically populate the ontology with instances obtained from LOD selected sources. The classes and properties of the ontology being created can be defined either directly, in terms of existing LOD-available classes and properties, or can be newly constructed by the domain expert. Ontology instances are then retrieved from the LOD datasets by executing suitable SPARQL queries. We illustrate our framework by creating Cancer Treatment ontology in the area of biomedicine.
Keywords :
SQL; ontologies (artificial intelligence); LOD datasets; LOD project; LOD selected sources; SPARQL queries; biomedicine; cancer treatment ontology; domain expert; domain ontology schema; domain-specific ontologies; knowledge-based applications; linking open data project; mOntage; ontology design; population framework; semantic-based applications; Cancer; Data mining; Drugs; Joining processes; Ontologies; Proteins; Resource description framework; Link Open Data; Ontology; Ontology Engineering; SPARQL;
Conference_Titel :
Semantic Computing (ICSC), 2013 IEEE Seventh International Conference on
Conference_Location :
Irvine, CA
DOI :
10.1109/ICSC.2013.21