Data Integration: A Logic-Based Perspective

AI Magazine. 26(1):59--70 2005.

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 these data. We discuss data integration 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 class-based representation formalism, and show that query answering in data integration, as well as all other relevant reasoning tasks, is decidable. However, the high computational complexity in the size of the data makes the use of a full-fledged expressive Description Logic infeasible in practice, when we have to deal with large amounts of data. 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.

@article{AI-magazine-2005,
   title = "Data Integration:  A Logic-Based Perspective",
   year = "2005",
   author = "Diego Calvanese and De Giacomo, Giuseppe",
   journal = "AI Magazine",
   pages = "59--70",
   number = "1",
   volume = "26",
   doi = "10.1609/aimag.v26i1.1799",
}