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论文编号：	14524
作者编号：	2120213458
上传时间：	2024/5/31 21:12:01
中文题目：	FAIR原则视角下我国自然科学数据平台建设评估与完善策略研究
英文题目：	Research on the Evaluation and Improvement Strategy of Chinese Natural Science Data Platform from the Perspective of FAIR Principle
指导老师：	肖雪副教授
中文关键字：	科学数据管理；FAIR原则；自然科学数据平台
英文关键字：	Scientific data management;FAIR principle;Natural science database
中文摘要：	科学数据是科研工作开展的重要基础资源，在当今知识大爆炸的背景下,科学数据也呈现几何式增长态势，但与其大规模增长与科研界日益重视利用的趋势相对应的是整体数据利用率低、资源难以有效保存等问题。为使科学数据创造更大价值，降低科研项目的重复性成本，近年来各国均努力发展科学数据管理项目。其中突出成就是于2016年欧洲发布的FAIR原则，该原则一经推出便引起广泛关注，并逐步在多个科学研究领域被推广运用，尤其是欧洲自然科学数据管理方面起步最早建树最多。近些年，FAIR原则在欧洲获得的良好运用逐渐被中国研究者关注并积极引入国内，但目前国内FAIR原则推广上仍是停留在学术研究领域，在实际科学数据管理政策和实践应用中少有体现。本研究希望通过初步评估了解目前自然科学数据平台在FAIR原则建设方面的发展情况，并通过与欧盟相关数据平台建设情况进行对比分析得出评估结果，再以深度案例分析的方式补足评估未涉及的建设领域，以此为基础提出国内数据平台FAIR化发展建议。 本研究首先梳理了目前国际具有知名度的FAIR指标体系，并以此为基础，结合国内数据平台建设实际情况，初步构造了本研究的FAIR指标评估体系，并以调查问卷形式邀请领域专家提出指标修改意见以完善指标及评分标准，通过多轮专家调查确定最终的FAIR原则建设情况评估指标体系。随后，本研究选取了由财政部与科技部共同支持建设的国家级自然科学数据平台（19家）作为国内评估对象，并随机选取在两大著名数据平台注册网站FAIRSharing和Re3data上注册的欧盟主导建设的自然科学数据平台（10家）作为欧盟评估对象，利用构造的FAIR指标体系对29家数据平台完成评估。从评估结果中发现国内虽然没有明确FAIR建设原则，但是其建设方向与FAIR原则相似，在具体原则建设中，国内数据平台在可查找性方面优于欧盟数据平台，可访问性方面与欧盟数据平台表现相似，而在可互操作性与可重用性方面相对表现不足。 在对评估中发现的问题进行梳理后，本研究认为其在整体规划、数据服务、技术支撑和数据使用方面薄弱，随后以所发现的问题为导向调查研究评估中表现突出的4家数据平台详细的发展建设情况，案例分析首先总述了4家数据平台的FAIR原则建设评估情况，其次通过横向比较四家数据平台建设情况、纵向调查研究挖掘各自发展特色，归纳总结出相关建设经验。最终，结合评估结果与案例分析情况，本研究认为应从宏观角度重视总体规划和资助策略建设，在中观角度应注重培养人才、制定无障碍方案，在微观层面应在检索方式、技术协议、机器可读模型等方面大力发展丰富数据服务。本研究图5幅，表18个，参考文献125篇。
英文摘要：	Scientific data is an important basic resource for scientific research. In the context of the knowledge explosion, scientific data also shows a geometric growth trend. However, its large-scale growth and the trend of increasing emphasis on the use of scientific research community are corresponding to the problems such as low overall data utilization rate and difficult to effectively preserve resources. In order to make scientific data create more value and reduce the repetitive cost of scientific research projects, all countries have made efforts to develop scientific data management projects in recent years. One of the outstanding achievements is the FAIR principle released in Europe in 2016, which has attracted wide attention since its launch and has gradually been promoted and applied in many scientific research fields, especially in the European natural science data management, which started the earliest and made the most achievements. In recent years, the good application of FAIR principle in Europe has gradually attracted the attention of Chinese researchers and been actively introduced into China. However, at present, the promotion of FAIR principle in China remains in the field of academic research and is rarely reflected in actual scientific data management policies and practical applications. This study hopes to understand the current development of natural science data platform in the construction of FAIR principles through preliminary evaluation, and draw evaluation results through comparative analysis with the construction of relevant data platforms in the European Union, and then make up for the construction areas not involved in the evaluation by way of in-depth case analysis, and on this basis, put forward suggestions for the development of domestic data platform FAIR. This study first sorted out the current internationally well-known FAIR index system, and on this basis, combined with the actual situation of domestic data platform construction, initially constructed the FAIR index evaluation system of this study, and invited experts in the field to put forward suggestions on index modification in the form of questionnaires to improve the index and scoring standards. The final evaluation index system of FAIR principle construction is determined through several rounds of expert investigation. Subsequently, this study selected 19 national natural science data platforms jointly supported by the Ministry of Finance and the Ministry of Science and Technology as domestic assessment objects, and randomly selected 10 natural science data platforms led by the European Union registered on the two famous data platform registration websites FAIRSharing and Re3data as EU assessment objects. The FAIR index system was used to evaluate 29 data platforms. From the evaluation results, it is found that although there is no clear FAIR construction principle in China, its construction direction is similar to FAIR principle. In the construction of specific principles, the domestic data platform is superior to the EU data platform in terms of searchability and accessibility, while the relative performance is insufficient in terms of interoperability and reusability. After reviewing the problems found in the evaluation, this study considers them weak in terms of overall planning, data services, technical support and data use. Then, guided by the problems found, a detailed investigation is conducted on the development and construction of the four data platforms with outstanding performance in the evaluation. The case analysis firstly summarizes the FAIR principle construction and evaluation of the four data platforms. Secondly, through horizontal comparison of the construction of the four data platforms, longitudinal investigation and research to excavate their respective development characteristics, and summarize the relevant construction experience. Finally, combined with the evaluation results and case analysis, this study believes that we should pay attention to the overall planning and funding strategy construction from the macro perspective, pay attention to the cultivation of talents and the formulation of barrier-free programs from the medium perspective, and vigorously develop rich data services in the aspects of retrieval methods, technical protocols and machine-readable models at the micro level. In this study, there are 5 figures, 18 tables and 125 references.
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