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Reconciling Practice and Rigour in Ontology-Based Heterogeneous Information Systems Construction

Abstract : Ontology integration addresses the problem of reconciling into one single semantic framework different knowledge chunks defined according to its own ontology. This field has been subject of analysis and many consolidated theoretical results are available. Still, in practice, ontology integration is difficult in heterogeneous information systems (HIS) that need to integrate assets already built and running which cannot be changed. Furthermore, in practice, the composed assets are usually not really defined according to an ontology but to a data model which is less rigorous but fit for the purpose of defining a data schema. In this paper, we propose a method for integrating assets participating in a HIS using a domain ontology, aimed at finding an optimal balance between semantic rigour and feasibility in terms of adoption in a real-world setting. The method proposes the use of data models describing the semantics of existing assets; their analysis in order to find commonalities and misalignments; the definition of the domain ontology, considering also other sources as standards, to express the main concepts in the HIS domain; the connection of the local models with this domain ontology; and its abstraction into a metamodel to facilitate further extensions. The method is an outcome of a collaborative software development project, OpenReq, aimed at delivering an ontology for requirements engineering (RE) designed to serve as baseline for the data model of an open platform offering methods and techniques to the RE community. The construction process of this ontology will be used to illustrate the method.
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Contributor : Hal Ifip <>
Submitted on : Friday, June 14, 2019 - 1:48:04 PM
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Carme Quer, Xavier Franch, Cristina Palomares, Andreas Falkner, Alexander Felfernig, et al.. Reconciling Practice and Rigour in Ontology-Based Heterogeneous Information Systems Construction. 11th IFIP Working Conference on The Practice of Enterprise Modeling (PoEM), Oct 2018, Vienna, Austria. pp.205-220, ⟨10.1007/978-3-030-02302-7_13⟩. ⟨hal-02156454⟩



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