The Role of Contextual Ontologies in Enterprise Modeling
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The Role of Contextual Ontologies in Enterprise Modeling

Authors: Ahmed Arara

Abstract:

Information sharing and exchange, rather than information processing, is what characterizes information technology in the 21st century. Ontologies, as shared common understanding, gain increasing attention, as they appear as the most promising solution to enable information sharing both at a semantic level and in a machine-processable way. Domain Ontology-based modeling has been exploited to provide shareability and information exchange among diversified, heterogeneous applications of enterprises. Contextual ontologies are “an explicit specification of contextual conceptualization". That is: ontology is characterized by concepts that have multiple representations and they may exist in several contexts. Hence, contextual ontologies are a set of concepts and relationships, which are seen from different perspectives. Contextualization is to allow for ontologies to be partitioned according to their contexts. The need for contextual ontologies in enterprise modeling has become crucial due to the nature of today's competitive market. Information resources in enterprise is distributed and diversified and is in need to be shared and communicated locally through the intranet and globally though the internet. This paper discusses the roles that ontologies play in an enterprise modeling, and how ontologies assist in building a conceptual model in order to provide communicative and interoperable information systems. The issue of enterprise modeling based on contextual domain ontology is also investigated, and a framework is proposed for an enterprise model that consists of various applications.

Keywords: Contextual ontologies, Enterprise model, domainontology.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1057475

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[1] Ahmed Arara, Djamal Benslimane, "Multi-perspectives Description of Large Domain Ontologies", In Christiansen et al. (Eds.), Proc. of FQAS-2004, June 2004, Lyon, France. Lecture Notes in Artificial Intelligence 3055 Springer 2004, pp.150-160.
[2] Aykut Firat, Stuart E. Madnick, and Benjamin Grosof, "Contextual Alignment of Ontologies for Semantic Interoperability ", MIT Sloan School of Management, MIT Sloan Working Paper 4515-04,CISL Working Paper 2004-17,October 2004.
[3] Baader et al, " The description Logic Handbook, Theory Implementation and Applications", Cambridge University Press, UK 2003, p555, ISBN 0521781760.
[4] Bouquet, et al., " C-OWL: Contextualizing Ontologies", In Proceedings of the 2nd International Semantic Web Conference (ISWC2003), LNCS 2870, 20-23 October 2003, Sundial Resort, Sanibel Island, Florida, USA.
[5] C. H. GOH, "Context Interchange: New Features and Formalisms for Intelligent Integration of Information", ACM Transactions on Information Systems, vol.17, no. 3, July1999, Pages 270-293.
[6] Chen, C.W., "An expert decision support system for monitoring and diagnosis of petroleum production and separation processes", Expert Systems with Applications,2005, 29, pp.131-143.
[7] N. Guarino, "Formal Ontology and Information Systems", In N. Guarino (ed.), Formal Ontology and Information Systems, Proc. Of the 1st International Conference, Trento, Italy, 6-8 June 1998.
[8] T. Strang, C. Linnhoff-popien, and K. Frank, " CoOL: A Context Ontology Language to enable contextual Interoperability" in the 4th IFIP International Conference on Distributed Applications and Interoperable Systems (DAIS2003, ser. Lecture Notes in Computer Science (LNCS), Paris/France: Springer, Nov. 2000.
[9] Mark S. Fox and Michael Gruninger, "Enterprise Modeling", American Association for Artificial Intelligence, 1998.
[10] Xiao Hang Wang, Da Qing Zhang, and Tao Gu, Hung Keng Pung," Ontology Based Context Modeling and Reasoning using OWL", Second IEEE Annual Conference on Pervasive Computing and Communications Workshops.
[11] F. Wolter and M. Zakharaschev, "Temporalizing description logic", in Proceedings of the 16 Th Int. Joint Conf. on Artificial Intelligence (IJCAI-99), pages 104-109, 1999.