安小米,许济沧,王丽丽,黄婕,胡菊芳.国际标准中的数据治理:概念、视角及其标准化协同路径[J].中国图书馆学报,2021,47(5):59~79
Data Governance in International Standards:Concepts,Perspectives and the Ways to Standardization Collaboration
国际标准中的数据治理:概念、视角及其标准化协同路径
Received:July 14, 2021  
DOI:
Key words:Data governance  Core concepts  International standards  Standardization collaboration
中文关键词:  数据治理  核心概念  国际标准  标准化协同路径
基金项目:本文系国家社会科学基金重大项目“我国政府数据治理与利用能力研究”(编号:20&ZD161)的研究成果之一
Author NameAffiliation
AN Xiaomi 中国人民大学信息资源管理学院 北京 100872 
XU Jicang 中国人民大学信息资源管理学院、香港城市大学数据科学学院 北京 100872 
WANG Lili 中国人民大学信息资源管理学院 北京 100872 
HUANG Jie 中国人民大学信息资源管理学院 北京 100872 
HU Jufang 中国人民大学图书馆 北京 100872 
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Abstract:
With the development of big data,Internet of Things and smart cities,data governance is becoming the core issues and concerns in the inter disciplined frontiers to ensure big data with 5v characteristics to assist intelligent decision making and value realization. This paper synthesizes concepts,perspectives and standardization collaboration model across international standardization organizations (SDOs). The study has many implications to standardization collaboration for the designing,directing,and monitoring the data governance plans and programs.
This paper collects many and various types of definitions of data governance from international standards organizations including ISO,IEC and ITU-T,then identifies core concepts and their relationships. Contents analysis of 19 relevant documents of standards have been conducted,mapping with core concepts,perspectives and concepts relationships of data governance. An analytical model for data governance standardization collaboration is proposed. It has provided a meta synthetic way of thinking to study multi dimensional (digital government,digital economy and digital society) and multi layer (macro,meso,micro) data governance standardization collaborationImplementation schemes of the USfederal government and European Committee have been analyzed under the proposed analytical model.
Through the analysis of definitions in different SDOs,it could be seen that data governance refers to strategic collaboration activities that design,direct and monitor the data management process,as well as the data asset value realization process. It includes the data related policies design and implementation. It also includes the unified strategic plan on data ownership and data stewardship. Through the analysis of perspectives of data governance,the paper proposes a three layered model,which helps data governors,data managers,and data workers design,direct and monitor their data related governance contents. Combined with the multi dimensional scenarios of data governance,a standardization collaboration model with 9 elements is synthesized. From the digital government dimension,the standardization collaboration model is composed of performance evaluation collaboration,data management process collaboration,data quality management collaboration,etc. From the digital economy dimension,the standardization collaboration model includes:data value chain and ecosystem strategic collaboration,data commercialization process collaboration,and data ownership and stewardship collaboration. From the digital society dimension,the standardization collaboration model includes:multiple stakeholders accountability collaboration,data platform construction collaboration,open data PDCA collaboration,data resource and service collaboration,and privacy and security protection collaborationThe case studies have following findings:the US. is inclusive on data governance,and the EU is conservative and passive on data governance.
China is recommended to optimize definitions of data governance to be more inclusive,as well as to develop and establish an integrated and coordinated data governance standardization system,which would harmonize,compatible and interoperable with those from different SDOs. 5 tabs. 5 figs. 69 refs.
中文摘要:
      本文收集三大国际权威标准组织ISO、IEC、ITU-T发布的标准文件中关于数据治理的各类定义,对数据治理的核心概念及其关系进行解构分析。基于数据治理的核心概念、概念关系及其视角进一步选择19个国际标准进行内容映射分析,构建出面向数字政府、数字经济和数字社会的数据治理标准化协同路径分析模型。依据该模型从多维度(数字政府、数字经济、数字社会)和多层级(宏观、中观和微观)归纳了美国和欧盟数据治理标准化协同路径的实施方案。本研究对于我国数据治理理论与实践具有以下现实价值和实践意义:推动我国积极参与数据治理领域国际规则和标准的制定,促进数据治理国家标准与国际标准的接轨;建立全视域的数据治理标准体系,构建基于“数字政府、数字经济、数字社会”的多场景、多层级的数据治理标准化协同路径及实施方案;构建数字治理标准化协同国家战略,促进多元主体共同参与数据治理标准建设。图5。表5。参考文献69。
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