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    Perspectives of Big Data Quality in Smart Service Ecosystems (Quality of Design and Quality of Conformance)


    Helfert, Markus (2018) Perspectives of Big Data Quality in Smart Service Ecosystems (Quality of Design and Quality of Conformance). Journal of Information Technology Management, 10 (4). pp. 72-83. ISSN 2008-5893

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    Abstract

    Despite the increasing importance of data and information quality, current research related to Big Data quality is still limited. It is particularly unknown how to apply previous data quality models to Big Data. In this paper we review Big Data quality research from several perspectives and apply a known quality model with its elements of conformance to specification and design in the context of Big Data. Furthermore, we extend this model and demonstrate it utility by analyzing the impact of three Big Data characteristics such as volume, velocity and variety in the context of smart cities. This paper intends to build a foundation for further empirical research to understand Big Data quality and its implications in the design and execution of smart service ecosystems.
    Item Type: Article
    Additional Information: Cite as: Helfert, M., Ge, M. (2018). 'Perspectives of Big Data Quality in Smart Service Ecosystems (Quality of Design and Quality of Conformance)', Journal of Information Technology Management, 10(4), pp. 72-83. doi: 10.22059/jitm.2019.72763
    Keywords: Big data quality; Information quality; Smart cities; Service design; Smart services; Data quality model; Smart service ecosystem;
    Academic Unit: Faculty of Social Sciences > School of Business
    Faculty of Social Sciences > Research Institutes > Innovation Value Institute, IVI
    Item ID: 14120
    Identification Number: 10.22059/JITM.2019.72763
    Depositing User: Markus Helfert
    Date Deposited: 03 Mar 2021 15:00
    Journal or Publication Title: Journal of Information Technology Management
    Publisher: Faculty of Management, University of Teheran
    Refereed: Yes
    Related URLs:
    URI: https://mu.eprints-hosting.org/id/eprint/14120
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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