数据与计算发展前沿 ›› 2025, Vol. 7 ›› Issue (3): 111-121.

CSTR: 32002.14.jfdc.CN10-1649/TP.2025.03.009

doi: 10.11871/jfdc.issn.2096-742X.2025.03.009

• 专刊：中国科学院计算机网络信息中心成立30周年 • 上一篇    下一篇

FAIR原则与数据密集型科学社区应用实践研究

姜恩波1,2,*(),方肖1,秦瑜1,2   

  1. 1.中国科学院成都文献情报中心，四川 成都 610041
    2.中国科学院大学，经济与管理学院，信息资源管理系，北京 100190
  • 收稿日期:2025-01-13 出版日期:2025-06-20 发布日期:2025-06-25
  • 通讯作者: *姜恩波（E-mail: jiangeb@clas.ac.cn）
  • 作者简介:姜恩波，中国科学院成都文献情报中心知识系统部副主任，中国科学院大学硕士生导师，正高级工程师。主要从事数字图书馆平台建设、知识组织、科学数据管理领域的研究与建设工作。近年来，主持或参与国家重点研发项目课题、四川省科技厅项目、中国科学院“十四五”文情能力专项、中国科学院“西部之光”项目，发表文章60多篇。曾在美国肯特州立大学图书情报学院作访问学者。
    本文负责提出研究思路，设计研究方案，进行案例分析与论文起草。
    JIANG Enbo is a senior engineer and the deputy director of the Knowledge Systems Department of Chengdu Library and Information Center, Chinese Academy of Sciences, master supervisor of University of Chinese Academy of Sciences. He mainly engages in the research and construction of digital library platforms, knowledge organization, and scientific data management. He has hosted or participated in national key research and development program projects, Sichuan Provincial Science and Technology Department projects, Fourteenth Five-Year Plan literature for information capacity special project and West Light Talent Program of the Chinese Academy of Sciences, and has published more than 60 papers. He has also served as a visiting scholar at the School of Library and Information Science at Kent State University in the United States.
    In this paper, he was primarily responsible for proposing the research ideas, designing the research plan, conducting case analysis, and drafting the manuscript.
    E-mail: jiangeb@clas.ac.cn
  • 基金资助:
    中国科学院文献情报能力建设专项——科技态势感知与分析能力建设

Research on the Application Practice of FAIR Principles in Data-Intensive Scientific Communities

JIANG Enbo1,2,*(),FANG Xiao1,QIN Yu1,2   

  1. 1. Chengdu Library and Information Center, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China
    2. Department of Information Resources Management, School of Economics and Management,University of Chinese Academy of Sciences, Beijing 100190, China
  • Received:2025-01-13 Online:2025-06-20 Published:2025-06-25

RichHTML

0

PDF

2

摘要：

【目的】数据密集型科学研究对数据具有高度依赖性。文章拟通过介绍FAIR原则与数据密集型科学嵌入融合的典型案例，推动FAIR原则理念的传播，同时为国内科学数据中心建设提供借鉴。【方法】以FAIR原则在欧盟开放数据门户、高能物理与地球科学社区的实践为例，探讨FAIR原则在数据管理中的建设性作用，总结数据密集型社区的建设经验。【结果】案例分析显示FAIR原则具有较好的兼容性、FAIR原则正跨越式地与人工智能领域相结合、FAIR原则的嵌入需要融入当前的数据基础设施与规范标准。【结论】FAIR原则已逐步被国际科研机构采纳，并在数据密集型科研领域验证了其有效性。相比之下，国内推广FAIR原则还需迎接制度、数据基础设施、FAIR跨界以及文化意识等诸多方面的挑战。

关键词: 数据密集型科学, FAIR原则, 应用实践, 数据管理

Abstract:

[Objective] Research in data-intensive sciences is highly dependent on data. This article aims to promote the dissemination of the concept of the FAIR principles by introducing typical cases of their integration into data-intensive science practices, while also providing a reference for the construction of scientific data centers in China. [Method] Taking the practice of the FAIR principles in the EU Open Data Portal, the High Energy Physics and Geoscience Community as examples, we explore the constructive role of the FAIR principles in data management and summarize the experience of building data-intensive communities. [Result] The case studies show that the FAIR Principles are of good compatibility and have been rapidly adopted in the field of AI. And also, the FAIR Principles need to be integrated into current data infrastructures and normative standards. [Conclusions] The FAIR principles have been gradually adopted by international scientific research institutions and demonstrated their effectiveness in data-intensive scientific research fields. In contrast, the promotion of the FAIR principles in China faces numerous challenges, including regulation, data infrastructure, cross-disciplinary FAIR implementation, and cultural awareness.

Key words: data intensive science, FAIR principles, application practice, data management