Data Integration: A Logic-Based Perspective

Authors

  • Diego Calvanese
  • Giuseppe De Giacomo

DOI:

https://doi.org/10.1609/aimag.v26i1.1799

Abstract

Data integration is the problem of combining data residing at different autonomous, heterogeneous sources and providing the client with a unified, reconciled global view of the data. We discuss dataintegration systems, taking the abstract viewpoint that the global view is an ontology expressed in a class-based formalism. We resort to an expressive description logic, ALCQI, that fully captures classbased representation formalisms, and we show that query answering in data integration, as well as all other relevant reasoning tasks, is decidable. However, when we have to deal with large amounts of data, the high computational complexity in the size of the data makes the use of a fullfledged expressive description logic infeasible in practice. This leads us to consider DL-Lite, a specifically tailored restriction of ALCQI that ensures tractability of query answering in data integration while keeping enough expressive power to capture the most relevant features of class-based formalisms.

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Published

2005-03-15

How to Cite

Calvanese, D., & De Giacomo, G. (2005). Data Integration: A Logic-Based Perspective. AI Magazine, 26(1), 59. https://doi.org/10.1609/aimag.v26i1.1799

Issue

Section

Articles