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A Semiotic Approach to Data Quality

  • Conference paper
Enterprise, Business-Process and Information Systems Modeling (BPMDS 2013, EMMSAD 2013)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 147))

Abstract

Since the introduction of the ER-language in the late seventies, data modeling has been an important aspect of information systems development. The quality of data models has been investigated since the mid-nineties. In another strand of research, data and information quality has been investigated even longer. Data can also be looked upon as a type of model (on the instance level), as illustrated e.g. in the product models in CAD-systems. In this paper we present a specialization of a general framework for assessing quality of models to be able to evaluate the combined quality of data models and data. A practical application of the framework from assessing the potential quality of different data sources to be used in a collaborative work environment is used for illustrating the usefulness of the framework. We find on the one hand that the traditional properties of data quality and data model quality is subsumed by the generic SEQUAL-framework, and that there are aspects in this framework that are not covered by the existing work on data and data model quality. On the other hand, the comparison has resulted in a useful deepening of the generic framework for data quality, and has in this way improved the practical applicability of the SEQUAL-framework when applied to discussing and assessing data quality.

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Author information

Authors and Affiliations

  1. Norwegian University of Science and Technology (NTNU), Norway

    John Krogstie

Authors
  1. John Krogstie
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Editor information

Editors and Affiliations

  1. University Paris 1 Pantheon-Sorbonne, Paris, France

    Selmin Nurcan

  2. Public Research Centre - Henri Tudor, Luxembourg-Kirchberg, Luxembourg

    Henderik A. Proper

  3. Information Systems, University of Haifa, Haifa, Israel

    Pnina Soffer

  4. Department of Computer and Information Science, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway

    John Krogstie

  5. Aalen University, Beethovenstraße 1, 73430, Aalen, Germany

    Rainer Schmidt

  6. INTI International University, Kuala Lumpur, Malaysia

    Terry Halpin

  7. Stockholm University/IbisSoft, Stockholm, Sweden

    Ilia Bider

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Krogstie, J. (2013). A Semiotic Approach to Data Quality. In: Nurcan, S., et al. Enterprise, Business-Process and Information Systems Modeling. BPMDS EMMSAD 2013 2013. Lecture Notes in Business Information Processing, vol 147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38484-4_28

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  • DOI: https://doi.org/10.1007/978-3-642-38484-4_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38483-7

  • Online ISBN: 978-3-642-38484-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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