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    Smart data analysis and data governance

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    Authors
    Feng, Yunzhong
    Feng, Xiaohua
    Affiliation
    Hebei Normal University
    University of Bedfordshire
    Issue Date
    2021-10-31
    Subjects
    data security law
    information security
    Smart chongli
    Big Data privacy
    data governance
    data protection regulation
    
    Metadata
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    Abstract
    Data governance is still an outstanding issue currently, especially in big data cases. There is a planned big event in 2022 at Chongli. A Smart Chongli has up and running. In order to run the event properly, information security protection should be taken into account. This research is to consider generalize this issue to the future, including the Smart Chongli winter event, but not only limited there. Because of many Smart Cities services are running by online devices, to protect their data, cyber security is in demand, for the Smart Cities' quantity. As a case study, Smart Chongli is discussed, in terms of participants' data. Analysis of these data needs to pay attention to the "Measures for the Administration of Data Security", "GDPR"and so on. Cyber security should be taken care of, from the start to its final ending. Nevertheless, for Smart Chongli, overall development and management need to consider data security impact. A solution is suggested to fill this gap, according to MKSmart trial project Phase 2 experience. Which could also be applied to other smart cities similar project for the time being. c 2021
    Citation
    Feng Y, Feng X (2021) 'Smart data analysis and data governance', CSAE 2021: The 5th International Conference on Computer Science and Application Engineering - Sanya, Association for Computing Machinery.
    Publisher
    Association for Computing Machinery
    URI
    http://hdl.handle.net/10547/625297
    DOI
    10.1145/3487075.3487112
    Additional Links
    https://dl.acm.org/doi/10.1145/3487075.3487112
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISBN
    9781450389853
    ae974a485f413a2113503eed53cd6c53
    10.1145/3487075.3487112
    Scopus Count
    Collections
    Computing

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