科研机构科学数据管理实践与展望

doi:10.19788/j.issn.2096-6369.190407

摘要/Abstract

摘要：

在数据密集型科研范式时代，科学数据成为全社会宝贵的学术资源，也是当代科技创新、科技竞争的重要战略资源，科学数据管理受到了国际组织、各国政府、科研资助机构、出版界、科研机构等不同层面主体的关注。尤其是位于科研前沿阵地的科研机构，既是科学数据的生产主体，又是科学数据直接利益主体，有义务承担起本机构科学数据的管理、共享保存与再利用等职责，为管理好全人类宝贵的科技资源发挥作用。目前科研机构产生的科学数据仍然存在分散于各项目组、课题组以及科研人员个体手中的问题，还未形成有效的管理与共享机制，机构层面科学数据管理能力还不成熟，需要进一步加强。为此，本文聚焦于科研机构数据管理问题，从数据管理政策和管理实践两个方面介绍了国内外科研机构层面科学数据管理进展，分析了科研机构科学数据管理框架，并重点阐述了中国农业科学院科学数据管理发展历程，包括农业科学数据库建设、科学数据中心（平台）建设和数据管理办法制定等方面。最后，基于前面的分析，从机构科学数据管理与科研信息化相结合、机构数据管理合作、基于科学大数据的科研发现、数据管理与分析人才培养等方面对我国科研机构科学数据管理提出展望，以期为我国其他科研机构的科学数据管理提供借鉴。

关键词: 科研机构, 科学数据, 数据管理, 政策, 科学数据管理, 数据管理办法

Abstract:

In the paradigm of data-intensive scientific research, the use of scientific data has become a valuable academic resource in society and an important strategic resource for technological innovation and competition. Scientific data management has attracted the attention of international organizations, governments, research-funding institutions, the publishing industry, scientific research institutions, and other subjects at different levels. In particular, scientific research institutions, which are at the forefront of scientific research, are not only the production subject of scientific data, but also a direct-interest subject of scientific data. These institutions are obliged to undertake the management, sharing, preservation, and reuse of their own scientific data, and play a role in the management of this precious scientific and technological resource for all humankind. At present, the scientific data generated by scientific research institutions are still scattered in the hands of various project groups, research groups, and individual researchers, and there is no effective management and sharing mechanism. The scientific data management capacity at the institutional level is immature and must be strengthened further. This paper focuses on scientific research institutions’ data management by introducing progress in scientific data management in scientific research institutions at home and abroad from two aspects of data management policy and management practice. The scientific data management framework of scientific research institutions is also analyzed, focusing on the Chinese Academy of Agricultural Sciences’ development process in their scientific data management, including an agricultural science database, scientific data center (platform), and data-management regulations. Finally, based on the previous analysis, this paper proposes scientific data management for scientific research institutions in China from the aspects of combining scientific data management and scientific research informatization, cooperation in institutional data management, scientific research discovery based on scientific big data, data management and analysis of personnel training to provide references for scientific data management in other Chinese scientific research institutions.

Key words: scientific research institutions, scientific data, data management, policy, scientific data management, data management methods

中图分类号:

G203

赵瑞雪, 赵华, 郑建华, 朱亮, 寇远涛. 科研机构科学数据管理实践与展望[J]. 农业大数据学报, 2019, 1(4): 65-75.

Ruixue Zhao, Hua Zhao, Jianhua Zheng, Liang Zhu, Yuantao Kou. Scientific Data Management in Scientific Research Institutions: Practice and Prospects[J]. Journal of Agricultural Big Data, 2019, 1(4): 65-75.

图/表 1

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