Abstract
Data integration is the problem of combining the data residing at different sources, and providing a unified view of these data, called global schema, which can be queried by the user. The interest in this kind of systems has been continuously growing in the last years. However, the design of a data integration system is a very complex task, and several issues remains open, including how to express the relation between the global schema and the sources, and how to process queries expressed on the global schema. In this paper we deal with these two problems, by presenting a logical framework for data integration, and by discussing the various choices for both the specification of a data integration system, and the design of query answering methods. Also, we elaborate on the observation that, in real world scenarios, the case of mutually inconsistent local databases will be very common, and we present the basic ideas in order to extend the integration framework with suitable nonmonotonic reasoning features for dealing with this case.
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Lenzerini, M. (2001). Data Integration Needs Reasoning. In: Eiter, T., Faber, W., Truszczyński, M.l. (eds) Logic Programming and Nonmotonic Reasoning. LPNMR 2001. Lecture Notes in Computer Science(), vol 2173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45402-0_4
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DOI: https://doi.org/10.1007/3-540-45402-0_4
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