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Contexts and Data Quality Assessment
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BibTeX
@MISC{Bertossi_contextsand,
author = {Leopoldo Bertossi and Flavio Rizzolo},
title = {Contexts and Data Quality Assessment},
year = {}
}
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Abstract
The quality of data is context dependent. Starting from this intuition and experience, we propose and develop a conceptual framework that captures in formal terms the notion of context-dependent data quality. We start by proposing a generic and abstract notion of context, and also of its uses, in general and in data management in particular. On this basis, we investigate data quality assessment and quality query answering as context-dependent activities. A context for the assessment of a database D at hand is modeled as an external database schema, with possibly materialized or virtual data, and connections to external data sources. The database D is put in context via mappings to the contextual schema, which produces a collection C of alternative clean versions of D. The quality of D is measured in terms of its distance to C. TheclassC is also used to define and do quality query answering. The proposed model allows for natural extensions, like the use of data quality predicates, the optimization of the access by the context to external data sources, and also the representation of contexts by means of more expressive ontologies.
Keyphrases
data quality assessment data source context dependent alternative clean version external database schema virtual data context-dependent activity data quality predicate context-dependent data quality formal term data management conceptual framework abstract notion expressive ontology contextual schema quality query answering natural extension
