Journal of Information Resources Management ›› 2024, Vol. 14 ›› Issue (2): 136-147.doi: 10.13365/j.jirm.2024.02.136

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Research and Construction Trends Analysis of Experimental Protocol Datafication

Fu Yun1,2 Zhu Liya1 Han Tao1,2 Zheng Xinman1,2 Liu Xiwen1,2   

  1. 1.National Science Library, Chinese Academy of Sciences, Beijing, 100190; 
    2. Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing, 100049
  • Online:2024-03-26 Published:2024-04-11
  • About author:Fu Yun, Ph.D. candidate, librarian, research interests include AI4Science, theory and methods of information science; Zhu Liya, M.S., assistant researcher, research interests include NLP, AI4Science; Han Tao, Ph.D. researcher, Master's supervisor, research interests include AI4Science, theory and methods of information science; Zheng Xinman, Ph.D. candidate, research interests include theory and methods of information science; Liu Xiwen (consponding author) Ph.D. researcher, Doctor's supervisor, research interests include AI4Science, theory and methods of information science.
  • Supported by:
    The work is supported by key program from National Natural Science Foundation of China“Data and Intelligence Empowered Theoretic Change of Scientific Information Resource and Knowledge Management Theory”(Grant No. 72234005), and general program from National Social Science Fund of China "The Study of Technological Library Knowledge Service Content Supporting AI4Science" (Grant No.22BTQ019).

Abstract: This study explores the trends in research and construction of experimental protocol datafication, aligning with the current needs of experimental protocols in scientific research. It redefines experimental protocols and clearly provides a clear conceptualization of their datafication. On this basis, the study conducts a comprehensive analysis of the national distribution, key research questions, and the leading institutions and researchers involved in 103 pieces of literature related to the experimental protocol datafication. The key research problem, focusing on the development of datasets (including corpora) with comprehensive integration and the characteristics of linking the upper and lower levels was selected for detailed analysis and analyzed. This involves categorizing and organizing the information into three types: scientific and technological literature database, computable data set and text annotation corpus. Building on this trend analysis, this study discusses the theoretical and methodological advantages that information resource management and knowledge service institutions can bring to four key research issues in experimental protocol datafication. It emphasizes their role in promoting the integration of theory and experiment and data-driven knowledge discovery.

Key words: Experimental protocols, Datafication, Data-driven knowledge discovery, Intelligent experimental platform, Theory and experiment integration

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