Composing Local-As-View Mappings: Closure and Applications
Authors
- Patricia C. Arocena (Department of Computer Science, University of Toronto, Canada)
- Ariel Fuxman (Microsoft Research, USA)
- Renée J. Miller (Department of Computer Science, University of Toronto, Canada)
Abstract
Schema mapping composition is a fundamental operation in schema mapping management and data exchange. The mapping composition problem has been extensively studied for a number a mapping languages, most notably source-to-target tuple-generating dependencies (s-t tgds). An important class of s-t tgds are LAV (local-as-view) tgds. This class of mappings is prevalent in practical data integration and exchange systems, and recent work by ten Cate and Kolaitis shows that it possesses desirable structural properties.
It is known that s-t tgds are not closed under composition. That is, given two mappings expressed with s-t tgds, their composition may not be definable by any set of s-t tgds (and, in general, may not be expressible in first-order logic). Despite their importance and extensive use in data integration and exchange systems, the closure properties of LAV composition remained open to date. The most important contribution of this paper is to show that LAV tgds are closed under composition, and provide an algorithm to directly compute the composition.
An important application of our composition result is that it helps to understand if given a LAV mapping M_{st} from schema S to schema T, and a LAV mapping M_{ts} from schema T back to S, the composition of M_{st} and M_{ts} is able to recover the information in any instance of S. Arenas et al. formalized this notion and showed that general s-t tgds mappings always have a recovery. Hence, a LAV mapping always has a recovery. However, the problem of testing whether a given M_{ts} is a recovery of M_{st} is known to be undecidable for general s-t tgds. In contrast, in this paper we show the tractability of the problem for LAV mappings, and give a polynomial-time algorithm to solve it.
Session
ICDT Research Session 6: Data Exchange 2 (Thursday, March 25, 11:00—12:30)