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Semantic Adaptation of Schema Mappings when Schemas Evolve

Cong Yu Dept. of EECS, Univ. of Michigan

Lucian Popa
IBM Almaden Research Center

Abstract
Schemas evolve over time to accommodate the changes in
the information they represent. Such evolution causes invalidation
of various artifacts depending on the schemas,
such as schema mappings. In a heterogenous environment,
where cooperation among data sources depends essentially
upon them, schema mappings must be adapted to reflect
schema evolution. In this study, we explore the mapping
composition approach for addressing this mapping adaptation
problem. We study the semantics of mapping composition
in the context of mapping adaptation and compare
our approach with the incremental approach of Velegrakis
et al [21]. We show that our method is superior in terms
of capturing the semantics of both the original mappings
and the evolution. We design and implement a mapping
adaptation system based on mapping composition as well
as additional mapping pruning techniques that significantly
speed up the adaptation. We conduct comprehensive experimental
analysis and show that the composition approach is
practical in various evolution scenarios. The mapping language
that we consider is a nested relational extension of
the second-order dependencies of Fagin et al [7]. Our work
can also be seen as an implementation of the mapping composition
operator of the model management framework.

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Tags: asymptotix

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