研究目的：

随着信息化和数字化的发展，科学数据的规模和复杂性不断增加，如何合理管理和利用科学数据成为各国政府及科研机构面临的重要问题。我国政府也逐步意识到科学数据政策的重要性，相继出台一系列相关政策文件，对科学数据的共享、开放等方面做出规定。自2005年国家出台相关政策第一次定义科学数据以来，截至2022年底，全国已有31个省（自治区、直辖市）相继出台了科学数据政策。本研究旨在通过对我国科学数据政策的部署及扩散进行分析，以揭示其发展历程、部署和扩散特征，为我国科学数据相关政策的制定提供重要参考。

研究方法：

基于政策工具理论，构建“政策工具——政策主体——数据生命周期”三维分析框架（即X维度、Y维度和Z维度），运用内容分析法与文献计量法对我国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；基于政策扩散理论，以我国部分国家层面政策以及省级层面科学数据政策作为研究对象，运用政策网络分析法与文献计量法探讨其扩散现象，追踪政策在国家机构、各省份之间的传播和推广情况。

研究结果：

政策部署方面：我国国家层面的科学数据政策在工具维度基本形成了“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。政策扩散方面：在时间维度上，我国科学数据政策采纳省份数量呈现S型形态；在空间维度上，呈现出“中间先行，两头跟进”的局面，且政策扩散具有邻近效应；在强度维度上，全国人民代表大会于2007年修订后的《中华人民共和国科学技术进步法》扩散强度最高；在广度维度上，国务院于2018年发布的《科学数据管理办法》扩散广度最高；在速度维度上，2018年是科学数据相关政策布局的重点推动年份，《中华人民共和国科学技术进步法》处于加速扩散阶段且政策效果持久，而《科学数据管理办法》的扩散速度在逐年下降；在方向维度上，通过政策网络分析和统计，发现我国科学数据政策的扩散方向整体呈现自上而下的层级扩散、国家层面的政府机构间的平行扩散和省级政府机构间的平行扩散等3种类型。

研究结论：

通过对我国科学数据政策部署结构和扩散特征分析，有以下发现：（1）在政策工具的使用中，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。（2）在科学数据领域高度统一的管理可能会缺乏专业性和灵活性。（3）政策对数据获取、数据处理阶段的部署较少，有进一步加大的空间。（4）我国科学数据政策扩散受到经济、治理、技术、横向压力、纵向压力等诸多因素的影响。基于此，本研究提出以下政策优化建议：（1）优化政策顶层设计，发挥国家政府行政指令作用，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。加强政策宣传和引导，营造有利于政策扩散的良好氛围。（2）切实简政放权，加强政策的领域、区域针对性，鼓励各省根据自身的独特优势和发展目标，在政策制定和实施过程中保持一定的独立性和创新性，探索适合当地的科学数据政策路径。（3）在科学数据政策制定过程中注重全生命周期管理，运用与各阶段特征及需求相契合的政策工具，进而逐步构建起涵盖全生命周期的科学数据政策体系。（4）拓展政策扩散模式，加强多方政策信息交流，通过优秀案例评选和通报、跨区域政府经验交流会等模式促进自上而下的层级扩散、国家层面政府机构间的平行扩散和地方政府机构间的平行扩散等3种类型之外的其他政策扩散路径，同时，应拓宽民意表达通道，进一步扩大科学数据政策制定的参与面。

Objective:

Scientific data is the basis of scientific research and innovation, and also an important resource to promote scientific and technological development and social progress. With the development of information technology and digitization, the scale and complexity of scientific data are increasing. How to manage and utilize scientific data reasonably has become an important issue faced by governments and scientific research institutions around the world. The Chinese government has gradually realized the importance of scientific data policy, and has successively issued a series of relevant policy documents to make provisions on the collection, sharing and opening of scientific data.

Since the national scientific data policy first defined scientific data in 2005, by the end of 2022, 31 provincial-level regions have successively issued scientific data policies. The purpose of this study is to analyze the evolution and diffusion of China’s scientific data policy, in order to reveal its development history, characteristics and trends, and provide important references for the formulation of China’s medical scientific data policy.

Methods:

Based on the theory of policy tools, this paper constructs a three-dimensional analysis framework of “policy tools -- policy issuing agency -- data life cycle” (i.e., X dimension, Y dimension and Z dimension), and deconstructs and quantifies 106 scientific data policies published at the national level from 2005 to 2022 by using content analysis and bibliometry. Based on the policy diffusion theory, some national policies and provincial scientific data policies in China are taken as research objects, and the diffusion phenomenon is discussed by using policy network analysis and bibliometric method, and the dissemination and promotion of policies among national institutions and provinces are tracked.

Results:

In terms of policy deployment: China’s national scientific data policy has basically formed a distribution pattern of “authority tool + capacity building tool” in the tool dimension; The State Council, the Ministry of Science and Technology and the People’s Congress shall, as main policy issuing agencies, make unified planning and management of scientific data; The policy aims to promote the use and sharing of data, while increasing investment in basic capacity building for scientific data development. In terms of policy diffusion: in the time dimension, the number of provinces adopting scientific data policy presents an S-shape; In the spatial dimension, there is a situation of “middle first, two ends follow”, and policy diffusion has proximity effect. In the diffusion intensity dimension, the Science and Technology Progress Law of the People’s Republic of China, revised by the National People’s Congress in 2007, has the highest diffusion intensity; In the diffusion breadth dimension, the Measures for the Management of Scientific Data released by The State Council in 2018 had the highest diffusion breadth; In the diffusion speed dimension, 2018 is the key year to promote the layout of policies related to scientific data. The Science and Technology Progress Law of the People’s Republic of China is in the stage of accelerating diffusion and the policy effect is lasting, while the diffusion speed of the Scientific Data Management Measures is decreasing year by year; In the direction dimension, through policy network analysis and statistics, it is found that the diffusion direction of scientific data policy in China presents three types: top-down diffusion, parallel diffusion among government agencies at the national level and parallel diffusion among provincial government agencies.

Conclusions:

Through the analysis of the policy deployment structure and diffusion characteristics of scientific data in China, the following findings are found: (1) In the use of policy tools, the absence of incentive tools, symbols and exhortation tools is serious, and the internal structure of policy tools is not balanced. (2) Highly unified management in the field of scientific data may lack professionalism and flexibility. (3) There is less deployment in the data collection and data processing phase, and there is room for further expansion. (4) The diffusion of scientific data policy in our country is influenced by many factors such as economy, governance, technology, horizontal pressure and vertical pressure. Based on the above research results, this study puts forward the following suggestions for policy optimization: (1) Optimize the top-level policy design, give play to the role of national government administrative instructions, appropriately increase the proportion of incentive tools, symbols and exhortations, and optimize the internal structure of various types of policy tools. It is also necessary to strengthen policy publicity and guidance and create a good atmosphere conducive to policy diffusion. (2) Effectively streamline administration and delegate power, strengthen the targeted areas and regions of policies, encourage provinces to maintain a certain degree of independence and innovation in the process of policy formulation and implementation according to their own unique advantages and development goals, and explore local scientific data policy paths. (3) Pay attention to the whole life cycle management in the process of scientific data policy formulation, and use policy tools that are compatible with the characteristics and needs of each stage, so as to gradually build a scientific data policy system covering the whole life cycle. (4) Expand the policy diffusion mode, strengthen multi-party policy information exchange, promote top-down hierarchical diffusion, parallel diffusion among government agencies at the national level and parallel diffusion among local government agencies through the selection and notification of excellent cases, cross-regional government experience exchange meetings and other modes of policy diffusion. At the same time, the channels for public opinion expression should be broadened, so as to expand the participation of scientific data policy making.