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Data Quality Evaluation: Methodology and Key Factors

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10699))

Abstract

Data Quality Evaluation is becoming an institutionalized stage in data quality lifecycle. More and more practice is promoted by data management and user organization in specific fields especially in better informationalized application circumstance.

In order to improve the ability of data quality evaluation, the paper presents the key factors for data quality assessment and measurement. On the base of analyzing the main methodologies and standards on data quality management, the key factors includes objectives, general principles, characteristics, measurement function etc.

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References

  1. DOD Guidelines on Data Quality Management (Summary), 31 July 2003

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  2. ISO/TS 8000:150 – A Framework for Data Quality Management (2011). http://www.dpadvantage.co.uk

  3. McGilvray, D.: Executing Data Quality Project, Ten Steps to Quality Data and Trusted Information (2008)

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  4. ISO/IEC DIS 25024 – Systems and Software Engineering - Systems and Software Quality Requirements and Evaluation - Measurement of Data Quality (2015)

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  5. Loshin, D.: The Practitioner’s Guide to Data Quality Improvement (2011)

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Correspondence to Bo Li .

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Yang, Y., Yuan, Y., Li, B. (2018). Data Quality Evaluation: Methodology and Key Factors. In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2017. Lecture Notes in Computer Science(), vol 10699. Springer, Cham. https://doi.org/10.1007/978-3-319-73830-7_22

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  • DOI: https://doi.org/10.1007/978-3-319-73830-7_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73829-1

  • Online ISBN: 978-3-319-73830-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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