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Journal of Library and Information Science in Agriculture ›› 2022, Vol. 34 ›› Issue (3): 37-50.doi: 10.13998/j.cnki.issn1002-1248.21-0574

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Research and Practice on Association of Scientific Data and Scientific Literature Oriented to Knowledge Service of Agricultural Industry

CHAI Miaoling1,2,3, ZOU Yixing4, TAN Rongzhi3,*, ZENG Yi5, REN Yunyue6   

  1. 1. Chengdu Documentation and Information Center, Chinese Academy of Sciences, Chengdu 610041;
    2. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190;
    3. TAN Rongzhi, Key Laboratory of Mountain Hazards and Earth Surface Process, Chinese Academy of Sciences, Chengdu 610041;
    4. Sichuan Rural Science and Technology Development Center, Chengdu 610042;
    5. Business school, City University of Hong Kong, Hong Kong 999077;
    6. School of Public Administration, Sichuan University, Chengdu 610065
  • Received:2021-07-23 Online:2022-03-05 Published:2022-04-27

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Abstract: [Purpose/Significance] In order to solve the problems of incomplete data chain and insufficient data support decision-making ability in agricultural science and technology management, this paper put forward a set of industrial knowledge service model based on the needs of scientific management in agriculture, and completed the key part of the model, the research and practice on association of scientific data and scientific literature. This study will provide theoretical and practical cases for library and information science (LIS) research institutions to serve agricultural science and technology management and industrial development. [Method/Process] Firstly, this paper reviews the current situation of research into knowledge service and data association. Secondly, based on the analysis of characteristics of industrial requirements and data management life cycle in agricultural science and technology management, the paper constructed a knowledge service model with industrial characteristics. Then, based on the agricultural science data and scientific literature of Sichuan Province, the study designed and constructed an ontology model and system based on industrial elements. [Results/Conclusions] 20 data types, 24 284 scientific data entries and related scientific literature were integrated. And we established multi-source heterogeneous data association in 1 system platform and 1 sub-platform with Chinese and English data. The research results will provide reference for cross-field cooperation between agricultural science and technology management and LIS research, and cross-departmental sharing of scientific data and scientific literature.

Key words: agricultural industry, scientific data, scientific literature, data association, ontology, industrial chain, big data

CLC Number: 

  • G353.1
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