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Models of Data Quality

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Information Technology for Management. Ongoing Research and Development (ISM 2017, AITM 2017)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 311))

Abstract

The research proposes a new approach to data quality management presenting three groups of DSL (Domain Specific Language). The first language group uses concept of data object in order to describe data to be analysed, the second group describes the requirements on data quality, and the third group describes data quality management process. The proposed approach deals with development of executable quality specifications for each kind of data objects. The specification can be executed step-by-step according to business process descriptions, ensuring the gradual accumulation of data in the database and data quality verification according to the specific use case.

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Acknowledgments

The research leading to these results has received funding from the research project “Competence Centre of Information and Communication Technologies” of EU Structural funds, contract No. 1.2.1.1/16/A/007 signed between IT Competence Centre and Central Finance and Contracting Agency, Research No. 1.8 “Data Quality Management by using Executable Business Process Models”.

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Authors and Affiliations

  1. SIA DIVI Grupa, Riga, Latvia

    Zane Bicevska & Ivo Oditis

  2. University of Latvia, Riga, Latvia

    Janis Bicevskis

Authors
  1. Zane Bicevska
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  2. Janis Bicevskis
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  3. Ivo Oditis
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Corresponding author

Correspondence to Ivo Oditis .

Editor information

Editors and Affiliations

  1. University of Economics in Katowice, Katowice, Poland

    Ewa Ziemba

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Bicevska, Z., Bicevskis, J., Oditis, I. (2018). Models of Data Quality. In: Ziemba, E. (eds) Information Technology for Management. Ongoing Research and Development. ISM AITM 2017 2017. Lecture Notes in Business Information Processing, vol 311. Springer, Cham. https://doi.org/10.1007/978-3-319-77721-4_11

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  • DOI: https://doi.org/10.1007/978-3-319-77721-4_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77720-7

  • Online ISBN: 978-3-319-77721-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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