大数据时代政府数据治理的政策分析
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摘要
[目的/意义]国家有关大数据治理的政策较为零散,没有形成统一规划,而学术界又缺少对相关政策的整体研究分析。因而文章致力于分析我国现有政府大数据治理政策的现状,以期完善政府大数据治理的政策体系。[方法/过程]构建了包括政策工具维度和大数据治理的核心概念体系维度在内的二维政策分析框架,采集了24份国内相关政策样本,通过87个内容分析单元的政策文本量化分析,对政策样本进行了统计和分析。[结果/结论]研究发现我国有关大数据时代政府数据治理政策绝大部分集中于中观层次,宏观层次的政策内容相对较少;从政策工具视角来看,供给面、环境面和需求面的政策内容较为均衡。
[Purpose/Significance]The country's policies on big data governance are relatively fragmented,and no unified planning has been formed,and the academic community lacks an overall analysis of related policies. Therefore,this paper aims to analyze the current status of China's existing government big data governance policies in order to improve the government's big data governance policy system.[Method/Process]This paper constructs a two-dimensional policy analysis framework including the dimension of policy tools and the dimension of big data governance content system. We collected 24 relevant policy samples,and quantified the policy texts of 87 content analysis units and analyzed the policy samples.[Result/Conclusion]The study finds that most of China's government data governance policies in the era of big data are concentrated in the middle level,and the content of policies at the macro level is relatively small. From the perspective of policy tools,the policy content of the supply side,the environment side,and the demand side is relatively balanced.
[Purpose/Significance]The country's policies on big data governance are relatively fragmented,and no unified planning has been formed,and the academic community lacks an overall analysis of related policies. Therefore,this paper aims to analyze the current status of China's existing government big data governance policies in order to improve the government's big data governance policy system.[Method/Process]This paper constructs a two-dimensional policy analysis framework including the dimension of policy tools and the dimension of big data governance content system. We collected 24 relevant policy samples,and quantified the policy texts of 87 content analysis units and analyzed the policy samples.[Result/Conclusion]The study finds that most of China's government data governance policies in the era of big data are concentrated in the middle level,and the content of policies at the macro level is relatively small. From the perspective of policy tools,the policy content of the supply side,the environment side,and the demand side is relatively balanced.
引文
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[2]推进大数据战略构筑网络强国[EB/OL].[2018-01-15].http://www.gov.cn/xinwen/2015-11/17/content_5013717.htm.
[3]决胜全面建成小康社会夺取新时代中国特色社会主义伟大胜利——在中国共产党第十九次全国代表大会上的报告[EB/OL].[2018-01-15]. http://www. mod. gov. cn/shouye/2017-10/27/content_4795953.htm.
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[5]安小米,郭明军,魏玮,等.大数据治理体系:核心概念、动议及其实现路径分析[J].情报资料工作,2018(1):6-11.
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[9] Martijn N,Hulstijn J,Bruijne M,et al.Determining the effects of data governance on the performance and compliance of enterprises in the logistics and retail sector[C]. International Federation for Information Processing,2015:454-466
[10] Panian Z. Some practical experiences in data governance[J].World Academy of Science,2010:939-946.
[11]刘桂锋,钱锦琳,卢章平.国内外数据治理研究进展:内涵、要素、模型与框架[J].图书情报工作,2017,61(22).137-144
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[16]张雅娴,苏竣.技术创新政策工具及其在我国软件产业中的应用[J].科研管理,2001(4):65-72.
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[18]苏竣.公共科技政策导论[M].北京:科学出版社,2014.
[19]陈劲.科学、技术与创新政策[M].北京:科学出版社,2013:285.
[20]谭开翠.现代公共政策导论[M].北京:中国书籍出版社,2013:108-109.
[21]郑大庆,黄丽华,张成洪,等.大数据治理的概念及其参考架构[J].研究与发展管理,2017,29(4):65-72.
[22]郑大庆,范颖捷,潘蓉,等.大数据治理的概念与要素探析[J].科技管理研究,2017,37(15):200-205.
[23]张绍华,潘蓉,宗宇伟.大数据治理与服务[M].上海:上海科学技术出版社,2016.
[24]桑尼尔·索雷思.大数据治理[M].北京:清华大学出版社,2013.
[25] Mohanapriya C,Bharathi K M,Aravinth S S,et al.A trusted data governance model for big data analytics[J].International Journal for Innovative Research in Science and Technology,2015,1(7):307-309.
[26] Loshin D.Chapter 5-data governance for big data analytics:Considerations for data policies and processes[M]//Big Data Analytics.Elsevier Inc.,2013:39-48.
[2]推进大数据战略构筑网络强国[EB/OL].[2018-01-15].http://www.gov.cn/xinwen/2015-11/17/content_5013717.htm.
[3]决胜全面建成小康社会夺取新时代中国特色社会主义伟大胜利——在中国共产党第十九次全国代表大会上的报告[EB/OL].[2018-01-15]. http://www. mod. gov. cn/shouye/2017-10/27/content_4795953.htm.
[4]实施国家大数据战略加快建设数字中国[EB/OL].[2018-01-15]. http://cpc. people. com. cn/n1/2017/1209/c64094-29696290.html.
[5]安小米,郭明军,魏玮,等.大数据治理体系:核心概念、动议及其实现路径分析[J].情报资料工作,2018(1):6-11.
[6]张宁,袁勤俭.数据治理研究述评[J].情报杂志.2017,36(5):129-134,163.
[7] Malik P.Governing big data:Principles and practices[J]. IBMJournal of Research and Development,2013,57(3):1-13.
[8] Bhansali N. Data governance:Creating value from information assets[M].CRC Press,2013:28-122.
[9] Martijn N,Hulstijn J,Bruijne M,et al.Determining the effects of data governance on the performance and compliance of enterprises in the logistics and retail sector[C]. International Federation for Information Processing,2015:454-466
[10] Panian Z. Some practical experiences in data governance[J].World Academy of Science,2010:939-946.
[11]刘桂锋,钱锦琳,卢章平.国内外数据治理研究进展:内涵、要素、模型与框架[J].图书情报工作,2017,61(22).137-144
[12]黄璜.美国联邦政府数据治理:政策与结构[J].中国行政管理,2017(8):47-56
[13]张明英,潘蓉.《数据治理白皮书》国际标准研究报告要点解读[J].信息技术与标准化,2015(6):54-57
[14]李鸣,郝守,勤何震.数据治理国际标准研究[J].信息技术与标准化,2017(Z1):48-52
[15]黄萃.政策文献量化分析[M].北京:科学出版社,2016
[16]张雅娴,苏竣.技术创新政策工具及其在我国软件产业中的应用[J].科研管理,2001(4):65-72.
[17]刘立.科技政策学研究[M].北京:北京大学出版社,2011.
[18]苏竣.公共科技政策导论[M].北京:科学出版社,2014.
[19]陈劲.科学、技术与创新政策[M].北京:科学出版社,2013:285.
[20]谭开翠.现代公共政策导论[M].北京:中国书籍出版社,2013:108-109.
[21]郑大庆,黄丽华,张成洪,等.大数据治理的概念及其参考架构[J].研究与发展管理,2017,29(4):65-72.
[22]郑大庆,范颖捷,潘蓉,等.大数据治理的概念与要素探析[J].科技管理研究,2017,37(15):200-205.
[23]张绍华,潘蓉,宗宇伟.大数据治理与服务[M].上海:上海科学技术出版社,2016.
[24]桑尼尔·索雷思.大数据治理[M].北京:清华大学出版社,2013.
[25] Mohanapriya C,Bharathi K M,Aravinth S S,et al.A trusted data governance model for big data analytics[J].International Journal for Innovative Research in Science and Technology,2015,1(7):307-309.
[26] Loshin D.Chapter 5-data governance for big data analytics:Considerations for data policies and processes[M]//Big Data Analytics.Elsevier Inc.,2013:39-48.