基于三维框架的我国科学数据政策文本内容分析

The Text Content Analysis of Chinese Scientific Data Policy Based on Three-Dimensional Framework

[目的/意义]分析我国国家层面发布的科学数据政策文本,描述国家层面政策部署特征,以期更好地把握科学数据政策的发展趋势,为我国科学数据相关政策的制定提供重要参考。[方法/过程]构建“政策工具—政策主体—数据生命周期”三维立体分析框架(即X维度、Y维度和Z维度),运用内容分析法与政策文本计量法对我国2005—2022年国家层面发布的106份科学数据政策进行解构和量化分析。[结果/结论]在政策工具维度基本形成“权威工具+能力建设工具”的分布模式;国务院、科技部、人民代表大会作为主要政策主体对科学数据统一规划和管理;政策致力于推动数据利用和共享,同时也在加大对科学数据发展的基本能力建设的投入。需要注意的是:激励工具、象征及劝诫工具缺位比较严重,且政策工具内部结构不够均衡;国务院、科技部、人民代表大会在科学数据管理方面负担较重;目前政策对数据获取、数据处理阶段的部署较少。建议适当增加激励工具和象征及劝诫工具的使用占比,优化各类型政策工具内部结构,切实简政放权,合理调节政策主体压力,加强科学数据全生命周期管理。

[Purpose/Significance]This paper analyzes the scientific data policy texts released at the national level in China and describes the characteristics of national policy deployment,intending to better grasp the development trend of scientific data policy and providing important references for the formulation of scientific data related policies in China.[Method/Process]Based on the three-dimensional analysis framework of“policy tool-policy subject-data lifecycle”(i.e.,X dimension,Y dimension,and Z dimension),the content analysis method and policy text measurement method were used to deconstruct and quantify 106 scientific data policies published at the national level from 2005 to 2022 in China.[Result/Conclusion]The distribution pattern of“authority policy tools+capacity policy building tools”is formed.The State Council,the Ministry of Science and Technology,and the People’s Congress,as the main subjects of scientific data policy,are making unified planning and management of scientific data.The scientific data policy aims to promote the use and sharing of data while increasing investment in basic capacity building for scientific data development.Notably,the absence of incentive tools,symbols,and exhortation tools is serious,and the internal structure of policy tools is not balanced.The State Council,the Ministry of Science and Technology,and the People’s Congress bear a heavy burden in scientific data management.The current policy has less deployment for the data acquisition and data processing stage.Proposals are given to increase the proportion of incentive tools and symbolic and exhorting tools,optimize the internal structure of various types of policy tools,effectively streamline administration and delegate power,rationally adjust the pressure of policy subjects,and strengthen the management of the whole lifecycle of scientific data.