A generic ontology development framework for data integration and decision support in a distributed environment

Abstract

Data inconsistency and data mismatch are critical problems that limit data interoperability and hinder smooth operation of a distributed business. An ontology represents a semantic model that explicitly describes various entities and their properties of a domain of discourse and acts as a vehicle for seamless data integration and exchange. The existing methodologies for ontology development fail to provide a comprehensive coverage for different steps, e.g. pre-development, development and post-development, which are necessary for successfully developing ontologies. We propose a generic and comprehensive methodology that puts ontology engineering on a firm scientific foundation and at the same time provides a collaborative environment for effective knowledge sharing and reuse. Furthermore, our approach also provides a way for automatically extracting frequent terms from the data to construct an ontology in a bottom-up fashion. The performance of our methodology has been evaluated by developing different ontologies to solve the real life applications, e.g. fault diagnosis and root cause investigation and spare parts maintenance.

Keywords:

• data integration and exchange
• knowledge management
• knowledge sharing and reuse
• ontology
• computer integrated manufacturing

Acknowledgements

The authors thank Pulak Bandyopadhyay for providing useful comments on the earlier drafts of the article, which helped to improve the quality. At the same time, the authors also thank Douglas Wolf (Worldwide Facilities Group, GM) for providing useful input to develop the equipment spare parts ontology.