Research on Methodology Framework for Big Data Governance System Building

  • An Xiaomi ,
  • Wang Lili
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  • 1. School of Information Resource Management, Renmin University of China, Beijing 100872;
    2. Key Laboratory of Data Engineering and Knowledge Engineering(Renmin University of China), Beijing 100872;
    3. E-government Research Center(Renmin University of China), Beijing 100872

Received date: 2019-03-24

  Revised date: 2019-08-14

  Online published: 2019-12-20

Abstract

[Purpose/significance] This paper aims to fill in the gaps in research that not enough attention is paid to the methodology for big data governance system building, and puts forward more generic methodology framework for construction of big data governance system.[Method/process] By defining concepts of methodology and the methodology framework, this paper systematically analyzes definitions of ISO and the relevant studies, identifies key components of methodology and the types of components and then proposes a methodology framework for construction of big data governance system. Based on given methodology framework, this paper analyzes the existing studies of big data governance system from 6 methodological components, including theory, conceptual model, principles and rules, processes and procedures, approaches and methods and the evaluation criteria. Based on the integration of key components of methodologies of big data governance system building, this paper recommends a Deming Cycle (PDCA) based approach for an integrated framework for big data governance system building.[Result/conclusion] The paper clarifies key issues of research about the existing methodology for big data governance system building,and provides a methodology framework for big data governance system building from a meta-synthetic research perspective.

Cite this article

An Xiaomi , Wang Lili . Research on Methodology Framework for Big Data Governance System Building[J]. Library and Information Service, 2019 , 63(24) : 43 -51 . DOI: 10.13266/j.issn.0252-3116.2019.24.005

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