Documentation, Informaiton & Knowledge ›› 2024, Vol. 41 ›› Issue (2): 150-160.doi: 10.13366/j.dik.2024.02.150

• Knowledge, Learning & Management • Previous Articles    

A Preliminary Study on the FAIRification Characteristics of China's National Scientific Data Center from the Perspective of Policy Text

YANG Heng1,2, LIU Fenghong1,2,3   

  1. 1. National Science Library, Chinese Academy of Sciences, Beijing,100191;
    2. Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing, 100191;
    3. School of Information Management, NanJing University, Nanjing, 210023
  • Online:2024-03-10 Published:2024-05-14
  • Contact: Correspondence should be addressed to LIU Fenghong,, ORCID: 0000-0002-3633-1464
  • Supported by:
    This is an outcome of the project "Effects of Data Papers on Data Sharing and Reuse"(2019M651797) supported by Post-doctoral Science Foundation of China, and the project "Publishing Model linked Research Paper and Scientific Data and its application in FAIR-compliant Manner"(23BXW097)supported by National Social Science Foundation of China.

Abstract: [Purpose/Significance] This paper explores the FAIRification characteristics of data policy of National Scientific Data Center in China, aiming to provide a preliminary reference of data management policy formulation and work optimization for them. [Design/Methodology] This paper comprehensively used the methods of network research and text mining. The content mining software, KH Coder, was employed to conduct quantitative text analysis of 79 data policies from 20 data centers. Through analyzing the frequency of FAIR principle appear in these policy texts and the words with high similarity used in FAIR principle of these policy texts, we revealed the attention difference and semantic feature of FAIR principle in different data centers and different types of policy texts. [Findings/Conclusion] The results show that the data policies of data centers have reflected some FAIR principles, but the attention to each principle is not balanced. Different types of data policies focus on different aspects of the FAIR principle, and the commonality lies in the findable principle and interoperable principle and a strong emphasis is given to metadata. [Originality/Value] This paper suggests that in the development of data policy, National Scientific Data Centers should highlight the role of "metadata" in data lifecycle management, promote the construction of data policy system driven by "data value-added" and appropriately introduce the FAIR principle based on the scientific data management practice in China.

Key words: Scientific data management, FAIR principles, National Scientific Data Center, Text mining