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中国农学通报 ›› 2017, Vol. 33 ›› Issue (11): 147-152.doi: 10.11924/j.issn.1000-6850.casb16050140

所属专题: 资源与环境 现代农业发展与乡村振兴 数字乡村

• 农业科技信息 • 上一篇    下一篇

大数据视角下农业科研信息资源共建共享模式探索

王 剑,吴定峰   

  1. (中国农业科学院农业信息研究所,北京 100081)
  • 收稿日期:2016-05-23 修回日期:2017-03-23 接受日期:2016-08-12 出版日期:2017-04-26 发布日期:2017-04-26
  • 通讯作者: 王剑
  • 基金资助:
    国家科技基础条件平台建设项目“国家农业科学数据共享中心”(2005DKA31800);中国农业科学院农业信息研究所科技创新工程项目“农业认知计算与超级计算研究”(CAAS-ASTIP-2016-AII)。

Construction and Sharing Mode of Agricultural Research Information Resources from the Perspective of Big Data

Wang Jian, Wu Dingfeng   

  1. (Agricultural Information Institute, CAAS, Beijing 100081)
  • Received:2016-05-23 Revised:2017-03-23 Accepted:2016-08-12 Online:2017-04-26 Published:2017-04-26

摘要: 随着农业科技创新活动的不断深入,农业科研信息的存储、挖掘、分析和共享等方面面临着巨大的压力。以大数据的视角,通过对农业科研大数据的共享与利用过程中存在问题的研究和探析,从中国农业科研大数据资源全局性、系统性出发,结合农业科研数据资源共享与利用的实践工作,围绕“存”、“用”和“管”等3个方面,探讨了农业科研大数据资源的共建与共享模式。根据农业科研大数据物理分布相对分散的特点,提出了大数据保存及使用分层的组织结构,据此提出了相关建议,旨在以此为提升中国农业科研大数据资源的共享与利用水平提供一些有益的参考。

关键词: 铁皮石斛, 铁皮石斛, 生物炭, 基质, 替代, 泥炭

Abstract: With deepening of science and technology innovation activities in the field of agriculture, agricultural research information storage, mining, analysis and sharing had faced enormous pressure. Through the deep excavation problems during the process of big data sharing and utilization for agricultural research, this paper combined practical work of sharing and use of agricultural scientific data resources and discussed on the construction and sharing mode of large data resources in agricultural research around the "deposit", "use" and "control" three aspects a global, systematic perspective from global, systematic perspective of big data in agriculture research. Due to large dispersion characteristics of agricultural research information, we designed the big data saving and management institutions structure which changed the traditional secondary data exchange mode of "data unit- data unit" to the third data management mode of “data unit-data storage management mechanism -data unit”. In the structure, we should build some data services platform to provide some kinds of data service, such as data provide services, data analytical services, data mining services, data extension services, and so on. To build data services platform, we could explore the practice mode that included pilot first, step on step, system design discussion, and construction services parallel to ensure data service quality. At the same time, we should focus on institutional building and construct to achieve integration mode which could build orderly top-level cooperation mode of different data platform. Based on these mechanisms that would be built, some construction standards which covered various fields and different themes should be built and all data would be updated dynamically in order to achieve the network information system intercommunication, resource sharing and information exchange. At last, we proposed some advices to enhance sharing and use of large data resources in agricultural research.

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