Adaptive search and selection of domain ontologies for reuse on the semantic web

Abstract

Ontology plays an important role in Semantic Web applications. However, building ontology remains challenging due to the time, cost an effort required. Several studies have proposed the reuse of existing ontologies when building new ones. However, some challenges remain: (1) locating relevant domain ontologies for reuse, (2) determining appropriate concepts for searching targeted ontologies and (3) understanding the discovered ontologies. This study presents an adaptive strategy for searching and selecting domain ontologies for reuse on the Semantic Web. The strategy relies on ontology-based and generic search engines, and predefined ontology features to locate existing domain ontologies and related data sources. The data sources provide ontologies’ specific concepts that enable their easy location over the Semantic Web. Finally, a set of criteria including semantic coverage, codification language, modularity and open availability are used to select the best reusable set of ontologies for the domain. The application of the framework in the e-government domain demonstrated its feasibility and yielded promising results