Semantic-Driven e-Government: Application of Uschold and King Ontology Building Methodology for Semantic Ontology Models Development

Electronic government (e-government) has been one of the most active areas of ontology developmentduring the past six years. In e-government, ontologies are being used to describe and specify e-governmentservices (e-services) because they enable easy composition, matching, mapping and merging of various egovernmentservices. More importantly, they also facilitate the semantic integration and interoperability ofe-government services. However, it is still unclear in the current literature how an existing ontologybuilding methodology can be applied to develop semantic ontology models in a government servicedomain. In this paper the Uschold and King ontology building methodology is applied to develop semanticontology models in a government service domain. Firstly, the Uschold and King methodology is presented,discussed and applied to build a government domain ontology. Secondly, the domain ontology is evaluatedfor semantic consistency using its semi-formal representation in Description Logic. Thirdly, an alignmentof the domain ontology with the Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE)upper level ontology is drawn to allow its wider visibility and facilitate its integration with existingmetadata standard. Finally, the domain ontology is formally written in Web Ontology Language (OWL) toenable its automatic processing by computers. The study aims to provide direction for the application ofexisting ontology building methodologies in the Semantic Web development processes of e-governmentdomain specific ontology models; which would enable their repeatability in other e-government projectsand strengthen the adoption of semantic technologies in e-government. The research would be of interest toe-government system developers as well as the Semantic Web community, as the framework and techniquesemployed to develop the semantic ontology models might be repeated in other domains of knowledge tobuild ontologies.