Implementation of Ontology Learning and Population System from Structured Data Sources: Standard-based Approach

Abstract

This paper proposes an ontology learning and population model from structured data sources. Recently various attempts have been made to harmonize Web 2.0 and the Semantic Web, named as Web 3.0 or Web 4.0. One of the most important issues for realization of the next Web platform is about how to make Web ontology rich as well as to address semantic interoperability between ontologies. To resolve those issues, Web ontology schemas should be precisely defined in semantic aspect and we should also develop a method for learning and population of ontology instances from diverse resources. This paper proposes a model which enables the ontology learning and population from structured data sources. The proposed model in this paper is a standard-based approach. In other words, our proposal is based on ISO/IEC 11179 - Metadata Registry, which is one of the international standards. This standard has been developed to support the interoperability between data by managing standardized common concepts. Therefore, our proposed model enhances the semantic interoperability between ontologies and enables the ontology enrichment from data sources.