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Ontology-Based Multidimensional Contexts with Applications to Quality Data Specification and Extraction

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Book cover Rule Technologies: Foundations, Tools, and Applications (RuleML 2015)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9202))

Abstract

Data quality assessment and data cleaning are context dependent activities. Starting from this observation, in previous work a context model for the assessment of the quality of a database was proposed. A context takes the form of a possibly virtual database or a data integration system into which the database under assessment is mapped, for additional analysis, processing, and quality data extraction. In this work, we extend contexts with dimensions, and by doing so, multidimensional data quality assessment becomes possible. At the core of multidimensional contexts we find ontologies written as Datalog\(^\pm \) programs with provably good properties in terms of query answering. We use this language to represent dimension hierarchies, dimensional constraints, dimensional rules, and specifying quality data. Query answering relies on and triggers dimensional navigation, and becomes an important tool for the extraction of quality data.

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Authors and Affiliations

  1. School of Computer Science, Carleton University, Ottawa, Canada

    Mostafa Milani & Leopoldo Bertossi

Authors
  1. Mostafa Milani
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  2. Leopoldo Bertossi
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Corresponding authors

Correspondence to Mostafa Milani or Leopoldo Bertossi .

Editor information

Editors and Affiliations

  1. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Nick Bassiliades

  2. University of Oxford, Oxford, United Kingdom

    Georg Gottlob

  3. Imperial College London, London, United Kingdom

    Fariba Sadri

  4. Freie Universität Berlin, Berlin, Germany

    Adrian Paschke

  5. SINTEF/University of Oslo, Oslo, Norway

    Dumitru Roman

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Milani, M., Bertossi, L. (2015). Ontology-Based Multidimensional Contexts with Applications to Quality Data Specification and Extraction. In: Bassiliades, N., Gottlob, G., Sadri, F., Paschke, A., Roman, D. (eds) Rule Technologies: Foundations, Tools, and Applications. RuleML 2015. Lecture Notes in Computer Science(), vol 9202. Springer, Cham. https://doi.org/10.1007/978-3-319-21542-6_18

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  • DOI: https://doi.org/10.1007/978-3-319-21542-6_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21541-9

  • Online ISBN: 978-3-319-21542-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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