Quantitative Evaluation of Big Data Policies from the Perspective of Information Process:Taking 11 National Big Data Policies as an Example
Hu Feng1,2, Wen Zhiqiang3, Shen Jinqiu1,2, Yao Yuan4
1.Jiangsu Academy of Science and Technology for Development,Nanjing 210042,China; 2.Jiangsu Information Institute of Science and Technology,Nanjing 210042,China; 3.College of Politics and Public Administration,Tianjin Normal University,Tianjin 300387,China; 4.College of Cultural Industries,Nanjing University of the Arts,Nanjing 210013,China
Abstract：This paper took 11 big data policies issued by central government departments from 2015 to 2019 as samples,and took Herring model as the research framework.It evaluated the big data policies quantitatively from the perspective of the process of identification,planning,collection,processing,analysis and demonstration of information needs.Based on the PMC index model,the PMC index value and depression degree of 11 big data policies were calculated,and the merits and demerits of each big data policy were evaluated concretely,and the referential policy improvement path were put forward.The result shows that the overall design of big data policies is scientific and reasonable,and the quality of policies is proven to be high.Among these policies,two policies' level are perfect,seven are excellent,and two are acceptable.However,the scores on the four factors of policy timeliness,policy tools,policy audience and policy content are low,which requires improvement in the future.
胡峰, 温志强, 沈瑾秋, 姚缘. 情报过程视角下大数据政策量化评价——以11项国家级大数据政策为例[J]. 中国科技论坛, 2020(4): 30-41.
Hu Feng, Wen Zhiqiang, Shen Jinqiu, Yao Yuan. Quantitative Evaluation of Big Data Policies from the Perspective of Information Process:Taking 11 National Big Data Policies as an Example. , 2020(4): 30-41.
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