Data-cleaning (or data-repairing) is considered a crucial problem in many database-related tasks. It consists in making a database consistent with respect to a set of given constraints. In recent years, repairing methods have been proposed for several classes of constraints. However, these methods rely on ad hoc decisions and tend to hard-code the strategy to repair conflicting values. As a consequence, there is currently no general algorithm to solve database repairing problems that involve different kinds of constraints and different strategies to select preferred values. In this paper we develop a uniform framework to solve this problem. We propose a new semantics for repairs, and a chase-based algorithm to compute minimal solutions. We implemented the framework in a DBMSbased prototype, and we report experimental results that confirm its good scalability and superior quality in computing repairs.

The Llunatic Data Cleaning Framework

MECCA, Giansalvatore;SANTORO, DONATELLO
2013-01-01

Abstract

Data-cleaning (or data-repairing) is considered a crucial problem in many database-related tasks. It consists in making a database consistent with respect to a set of given constraints. In recent years, repairing methods have been proposed for several classes of constraints. However, these methods rely on ad hoc decisions and tend to hard-code the strategy to repair conflicting values. As a consequence, there is currently no general algorithm to solve database repairing problems that involve different kinds of constraints and different strategies to select preferred values. In this paper we develop a uniform framework to solve this problem. We propose a new semantics for repairs, and a chase-based algorithm to compute minimal solutions. We implemented the framework in a DBMSbased prototype, and we report experimental results that confirm its good scalability and superior quality in computing repairs.
2013
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/55464
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