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Schema mapping coverage

Schema mapping coverage In this paper, we introduce and study schema mapping coverage for relational databases. Given a relational schema mapping in the presence of both source dependencies and target dependencies, the coverage problem is to decide and describe which source instances have solutions under the mapping. Our main motivation is to describe limitations of schema mappings and hence to effectively determine if the mappings can fulfill their user expectations for the given tasks. We first propose using database dependencies to model user expectations of schema mappings. Then we formally define the notion of schema mapping coverage and propose using a set of dependencies in the source schema language to represent coverage. We look into how target dependencies indirectly enforce dependencies via mapping specifications on source instances and thus determine which source instances have solutions. We prove that the problem of computing schema mapping coverage is undecidable in general. We present algorithms for computing coverage for schema mappings where both the source dependencies and the target dependencies consist of functional dependencies and acyclic inclusion dependencies. Schema mapping coverage describes the ability to map source instances to target instances for mappings, it provides a way to describe limitations of schema mappings, which can be especially useful for mapping design and evolution. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Mathematics and Artificial Intelligence Springer Journals

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References (22)

Publisher
Springer Journals
Copyright
Copyright © Springer Nature Switzerland AG 2021
ISSN
1012-2443
eISSN
1573-7470
DOI
10.1007/s10472-020-09720-4
Publisher site
See Article on Publisher Site

Abstract

In this paper, we introduce and study schema mapping coverage for relational databases. Given a relational schema mapping in the presence of both source dependencies and target dependencies, the coverage problem is to decide and describe which source instances have solutions under the mapping. Our main motivation is to describe limitations of schema mappings and hence to effectively determine if the mappings can fulfill their user expectations for the given tasks. We first propose using database dependencies to model user expectations of schema mappings. Then we formally define the notion of schema mapping coverage and propose using a set of dependencies in the source schema language to represent coverage. We look into how target dependencies indirectly enforce dependencies via mapping specifications on source instances and thus determine which source instances have solutions. We prove that the problem of computing schema mapping coverage is undecidable in general. We present algorithms for computing coverage for schema mappings where both the source dependencies and the target dependencies consist of functional dependencies and acyclic inclusion dependencies. Schema mapping coverage describes the ability to map source instances to target instances for mappings, it provides a way to describe limitations of schema mappings, which can be especially useful for mapping design and evolution.

Journal

Annals of Mathematics and Artificial IntelligenceSpringer Journals

Published: Jan 2, 2021

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