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Assessing Data Quality: An Approach for the Spread of COVID-19

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Recent Challenges in Intelligent Information and Database Systems (ACIIDS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1863))

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Abstract

The work aims to develop a method for assessing the quality of publicly available data collections on the spread of the COVID-19 pandemic with daily infection statistics, recoveries and deaths. The World Health Organization, European Center for Disease Prevention and Control, Johns Hopkins University and Ministry of Health of the Republic of Poland provide this data as proof of concept. Metrics have been proposed that describe the most important quality features for this type of data collection - accuracy, completeness and consistency. Additional measures have also been defined based on anomaly detection, credibility and correlation between sets. A quality assessment method has been developed that uses specific metrics. The effectiveness of measures was tested on original and modified data. The findings showed that the measures were defined correctly. The method assigns lower-quality categories to datasets containing irregularities and higher for data with fewer errors.

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Acknowledgments

Part of the work presented in this paper received financial support from the statutory funds at the Wrocław University of Science and Technology.

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Authors and Affiliations

  1. Department of Applied Informatics, Wroclaw University of Science and Technology, Wroclaw, Poland

    Dariusz Król

  2. Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wroclaw, Poland

    Anna Bodek

Authors
  1. Dariusz Król
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  2. Anna Bodek
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Corresponding author

Correspondence to Dariusz Król .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand

    Siridech Boonsang

  3. Iwate Prefectural University, Iwate, Japan

    Hamido Fujita

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Bogumiła Hnatkowska

  5. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  6. King Mongkut's Institute of Technology, Ladkrabang, Thailand

    Kitsuchart Pasupa

  7. Malaysia Japan International Institute of Technology, Kuala Lumpur, Malaysia

    Ali Selamat

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Król, D., Bodek, A. (2023). Assessing Data Quality: An Approach for the Spread of COVID-19. In: Nguyen, N.T., et al. Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2023. Communications in Computer and Information Science, vol 1863. Springer, Cham. https://doi.org/10.1007/978-3-031-42430-4_18

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  • DOI: https://doi.org/10.1007/978-3-031-42430-4_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-42429-8

  • Online ISBN: 978-3-031-42430-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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