Converting a controlled vocabulary into an ontology

Paper by Jian Qin & Stephen Paling, School of Information Studies.

The prevalance of digital information raised issues regarding the suitability of conventional library tools for organizing information. The multi-dimensionality of digital resources requires a more versatile and flexible representation to accommodate intelligent information representation and retrieval. Ontologies are used as a solution to such issues in many application domains, mainly due to their ability explicitly to specify the semantics and relations and to express them in a computer understandable language. Conventional knowledge organization tools such as classifications and thesauri resemble ontologies in a way that they define concepts and relationships in a systematic manner, but they are less expressive than ontologies when it comes to machine language. This paper used the controlled vocabulary at the Gateway to Educational Materials (GEM) as an example to address the issues in representing digital resources. The theoretical and methodological framework in this paper serves as the rationale and guideline for converting the GEM controlled vocabulary into an ontology. Compared to the original semantic model of GEM controlled vocabulary, the major difference between the two models lies in the values added through deeper semantics in describing digital objects, both conceptually and relationally.

thanks infodesign and victor lombardi