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Open data: Quality over quantity

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  • Sadiq, Shazia
  • Indulska, Marta

Abstract

Open data aims to unlock the innovation potential of businesses, governments, and entrepreneurs, yet it also harbours significant challenges for its effective use. While numerous innovation successes exist that are based on the open data paradigm, there is uncertainty over the data quality of such datasets. This data quality uncertainty is a threat to the value that can be generated from such data. Data quality has been studied extensively over many decades and many approaches to data quality management have been proposed. However, these approaches are typically based on datasets internal to organizations, with known metadata, and domain knowledge of the data semantics. Open data, on the other hand, are often unfamiliar to the user and may lack metadata. The aim of this research note is to outline the challenges in dealing with data quality of open datasets, and to set an agenda for future research to address this risk to deriving value from open data investments.

Suggested Citation

  • Sadiq, Shazia & Indulska, Marta, 2017. "Open data: Quality over quantity," International Journal of Information Management, Elsevier, vol. 37(3), pages 150-154.
    • Handle: RePEc:eee:ininma:v:37:y:2017:i:3:p:150-154
    DOI: 10.1016/j.ijinfomgt.2017.01.003
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    References listed on IDEAS

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    1. Peter B. Seddon, 1997. "A Respecification and Extension of the DeLone and McLean Model of IS Success," Information Systems Research, INFORMS, vol. 8(3), pages 240-253, September.
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    Cited by:

    1. Hou, Jianhua & Wang, Yuanyuan & Zhang, Yang & Wang, Dongyi, 2022. "How do scholars and non-scholars participate in dataset dissemination on Twitter," Journal of Informetrics, Elsevier, vol. 16(1).
    2. Barbara Å libar & Dijana OreÅ¡ki & Nina BegiÄ ević ReÄ‘ep, 2021. "Importance of the Open Data Assessment: An Insight Into the (Meta) Data Quality Dimensions," SAGE Open, , vol. 11(2), pages 21582440211, June.
    3. Ruojing Zhang & Marta Indulska & Shazia Sadiq, 2019. "Discovering Data Quality Problems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(5), pages 575-593, October.
    4. Jinhua Chu & You-Yu Dai & Anyuan Zhong, 2023. "Factors Influencing the Effectiveness of Open Government Data Platforms: A Data Analysis of 61 Prefecture-Level Cities in China," SAGE Open, , vol. 13(3), pages 21582440231, August.

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    Keywords

    Open data; Data quality;

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