农业图书情报学报 ›› 2022, Vol. 34 ›› Issue (3): 37-50.doi: 10.13998/j.cnki.issn1002-1248.21-0574

• 研究论文 • 上一篇    下一篇

面向农业产业知识服务的科学数据与科技文献关联研究与实践

柴苗岭1,2,3, 邹弈星4, 谭荣志3,*, 曾怡5, 任运月6   

  1. 1.中国科学院 成都文献情报中心,成都 610041;
    2.中国科学院大学 经济与管理学院,北京 100190;
    3.中国科学院 山地灾害与地表过程重点实验室,成都 610041;
    4.四川省农村科技发展中心,成都 610042;
    5.香港城市大学 商学院,香港 999077;
    6.四川大学 公共管理学院,成都 610065
  • 收稿日期:2021-07-23 出版日期:2022-03-05 发布日期:2022-04-27
  • 通讯作者: *谭荣志,工程师,中国科学院水利部成都山地灾害与环境研究所,研究方向为数据资源管理、山地灾害防灾减灾。Email:tanrz@imde.ac.cn
  • 作者简介:柴苗岭,博士研究生,副研究馆员,中国科学院成都文献情报中心,研究方向为资源建设、知识组织、知识产权情报研究。邹弈星,硕士,副研究员,四川省农村科技发展中心,研究方向为农业科技管理。曾怡,博士研究生,香港城市大学商学院信息系统系,研究方向为知识组织技术、知识管理。任运月,博士研究生,四川大学公共管理学院图书馆学,研究方向为信息管理方法与应用
  • 基金资助:
    中国科学院“山地灾害与地表过程重点实验室开放基金”; 中国科学院文献情报能力建设专项“开放知识资源体系建设(二期)”(Y1755); 四川省科技计划国际合作项目“面向知识服务的农业科学数据和科技文献关联融汇服务系统研究与示范”(2017HH0094)

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

摘要: [目的/意义]为解决当前农业科技管理中广泛存在数据链不完整,数据支撑决策能力不足的情况,本文提出了一套从农业科技管理需求出发的产业知识服务模型,并就其中的关键环节科学数据和科技文献关联进行了研究和实践,以期为图书情报机构服务农业科技管理和产业发展提供理论与实践案例。[方法/过程]本文首先梳理了知识服务和数据关联现状,其次在分析农业科技管理中的产业需求特征和数据管理生命周期的基础上,构建了包含产业特征的知识服务模型,然后以四川农业科学数据和科技文献为基础,从产业要素出发,设计了本体模型和系统,最后完成实践。[结果/结论]研究最后集成20个数据类型,24 284条科学数据和科技文献,1个系统平台和1个子平台,建立了多源异构、中英两语种的数据关联,实现了基于产业知识服务的科学数据和科技文献关联和平台交流。研究成果将对农业科技管理与图书情报学跨领域合作,科学数据和科技文献跨部门共享提供借鉴。

关键词: 农业产业, 科学数据, 科技文献, 数据关联, 本体, 产业链, 大数据

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

中图分类号: 

  • G353.1

引用本文

柴苗岭, 邹弈星, 谭荣志, 曾怡, 任运月. 面向农业产业知识服务的科学数据与科技文献关联研究与实践[J]. 农业图书情报学报, 2022, 34(3): 37-50.

CHAI Miaoling, ZOU Yixing, TAN Rongzhi, ZENG Yi, REN Yunyue. Research and Practice on Association of Scientific Data and Scientific Literature Oriented to Knowledge Service of Agricultural Industry[J]. Journal of Library and Information Science in Agriculture, 2022, 34(3): 37-50.