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A Knowledge Representation and Data Provenance Model to Self-Tuning Database Systems

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3 Author(s)
Almeida, A.C. ; Dept. de Inf., PUC-Rio, Rio de Janeiro, Brazil ; Lifschitz, S. ; Breitman, K.

Most autonomic database systems do not explicit their decision rationale behind tuning activities. Consequently, users may not trust some of the automatic tuning decisions. In this paper we propose a rather transparent strategy, that provides feedback to database administrators, based on information extracted from the database log. The proposed approach consists in transforming log results into a user-friendly knowledge representation, based on the graphical representation for OWL. This model provides users with the rationale behind system decisions, adds semantics to the database self-tuning actions, and provides useful provenance information about the whole process.

Published in:

Software Engineering Workshop (SEW), 2009 33rd Annual IEEE

Date of Conference:

13-14 Oct. 2009