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Journal of Information Science and Engineering, Vol. 29 No. 5, pp. 851-871 (September 2013)


Ontology Evolution and Challenges*


ASAD MASOOD KHATTAK1, RABIA BATOOL1, ZEESHAN PERVEZ1, ADIL MEHMOOD KHAN2 AND SUNGYOUNG LEE1,+
1Department of Computer Engineering
Kyung Hee University
Yongin, 446-701 Korea
2Division of Information and Computer Engineering
Ajou University
Gyeonggi-do, 443-749 Korea

Information semantics and semantic interoperability among applications, systems, and services are mostly based on ontology. Its increase usage in Information Systems and Knowledge Sharing Systems raises the importance of ontology maintenance. Ontology change management incorporates areas like ontology engineering, evolution versioning, merging, integration, and maintenance. Changes are made to the body of knowledge as experts develop a better understanding of the domain. As a result, the body of knowledge evolves from one state to another. Preserving consistency, while accommodating new changes, is a crucial task that needs special attention. This paper aims at providing a comprehensive review on key approaches followed in the field of ontology evolution. The analysis reveals that different individual components have been developed but a complete integrated system for automated ontology evolution is not available yet. This paper introduces some unfolded challenges in the field of ontology evolution, which must be tackled to complete the process automatically. Moreover, the new changes could affect the dependent data, applications, systems, and services. Therefore, this paper also discusses in detail why special attention must be paid to minimize the after effects of ontology evolution and proposes some possible solutions to achieve this goal.

Keywords: knowledge management, knowledge management applications, ontology, ontology change, ontology change management, ontology evolution

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Received July 29, 2011; revised May 24, 2012; accepted December 6, 2012.
Communicated by Elena Garcia-Barriocanal.
+ Corresponding author.
* This research was supported by the MKE (The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2012-(H0301-12-2001)). This work was supported by the Industrial Strategic Technology Development Program (10035348, Development of a Cognitive Planning and Learning Model for Mobile Platforms) funded by the Ministry of Knowledge Economy (MKE, Korea). This research was supported by the new faculty research fund of Ajou University. This paper is supported by sabbatical year of Kyung Hee University in 2010.