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Measuring and Computing Database Inconsistency via Repairs

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Scalable Uncertainty Management (SUM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11142))

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Abstract

We propose a generic numerical measure of inconsistency of a database with respect to a set of integrity constraints. It is based on an abstract repair semantics. A particular inconsistency measure associated to cardinality-repairs is investigated; and we show that it can be computed via answer-set programs.

L. Bertossi—Member of the “Millenium Institute for Foundational Research on Data” (IMFD, Chile). Research supported by NSERC Discovery Grant #06148.

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Notes

  1. 1.

    Abstract distances between two point-sets are investigated in [8], with their computational properties. Our setting is a particular case.

  2. 2.

    For INDs repairs based only on tuple deletions can be considered [6].

  3. 3.

    Other possible measures for single FDs and relationships between them can be found in [11].

  4. 4.

    For certain forms of prioritized repairs, such as endogenous repairs, the normalization coefficient |D| might be unnecessarily large. In this particular case, it might be better to use \(|D^n|\).

  5. 5.

    This approach was followed in [1] to compute maximum responsibility degrees of database tuples as causes for violations of DCs, appealing to a causality-repair connection [3].

  6. 6.

    Certain (or skeptical) reasoning with repair programs for DCs with weak constraints is \(\varDelta ^P_2({ log}(n))\)-complete in data complexity, i.e. in the size of the database [7, 12].

References

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Authors and Affiliations

  1. Carleton University, Ottawa, Canada

    Leopoldo Bertossi

  2. RelationalAI, Inc., Berkeley, USA

    Leopoldo Bertossi

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  1. Leopoldo Bertossi
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Correspondence to Leopoldo Bertossi .

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Editors and Affiliations

  1. University of Milano-Bicocca, Milan, Italy

    Davide Ciucci

  2. University of Milano-Bicocca, Milan, Italy

    Gabriella Pasi

  3. Sapienza University of Rome, Rome, Italy

    Barbara Vantaggi

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Bertossi, L. (2018). Measuring and Computing Database Inconsistency via Repairs. In: Ciucci, D., Pasi, G., Vantaggi, B. (eds) Scalable Uncertainty Management. SUM 2018. Lecture Notes in Computer Science(), vol 11142. Springer, Cham. https://doi.org/10.1007/978-3-030-00461-3_26

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  • DOI: https://doi.org/10.1007/978-3-030-00461-3_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00460-6

  • Online ISBN: 978-3-030-00461-3

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