MS-ONTO - Model and System for Supporting Ontology Evolution

Emile Tawamba, Roger Nkambou, Bernabé Batchakui, Claude Tangha

2014

Abstract

Ontology is becoming the key knowledge capture structure in many domains. It plays a very important role in the area of semantic web and is widely used in multiple fields including Intelligent Tutoring Systems (ITS) and e-Learning. Ontologies are intensively used in domain knowledge modeling in specific areas which can evolve. However, current tools used to implement ontologies fail to provide functions to adequately ensure their evolution. To deal with this issue, we have developed an ontology evolution management system named «MS-ONTO», founded on a formal description of evolution operators. MS-ONTO allows the preservation of both the internal and external integrity constraints during the ontology evolution: the external integrity meaning the preservation of its usage while internal integrity means its conformity to the constraints (implicit or explicit) related to the ontology model itself. MS-ONTO should be integrated as a plug-in in existing ontology editors such as NeOn Toolkit and Protégé.

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Paper Citation


in Harvard Style

Tawamba E., Nkambou R., Batchakui B. and Tangha C. (2014). MS-ONTO - Model and System for Supporting Ontology Evolution . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014) ISBN 978-989-758-049-9, pages 319-326. DOI: 10.5220/0005085203190326


in Bibtex Style

@conference{keod14,
author={Emile Tawamba and Roger Nkambou and Bernabé Batchakui and Claude Tangha},
title={MS-ONTO - Model and System for Supporting Ontology Evolution},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014)},
year={2014},
pages={319-326},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005085203190326},
isbn={978-989-758-049-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014)
TI - MS-ONTO - Model and System for Supporting Ontology Evolution
SN - 978-989-758-049-9
AU - Tawamba E.
AU - Nkambou R.
AU - Batchakui B.
AU - Tangha C.
PY - 2014
SP - 319
EP - 326
DO - 10.5220/0005085203190326