农业农村社会经济数据:资源与方法

数据重用影响因素对仓储型数据管理平台发展方向的启示

  • 孙雨潇 ,
  • 李艳丽 ,
  • 李峰 ,
  • 李斌
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  • 1.中国农业科学院农业环境与可持续发展研究所, 北京 100081,中国
    2.北京市农林科学院林业果树研究所, 北京 100093,中国
孙雨潇,E-mail:sunyuxiao@caas.cn

收稿日期: 2023-07-16

  录用日期: 2023-08-02

  网络出版日期: 2023-11-14

基金资助

中央级公益性科研院所基本科研业务费专项(BSRF202315)

The Enlightenment of Factors Influencing Data Reuse on the Development Direction of Warehouse-Based Data Management Platforms

  • YuXiao SUN ,
  • YanLi LI ,
  • Feng LI ,
  • Bin LI
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  • 1. Institute of Environment and Sustainable Development in Agriculture,Chinese Academy of Agricultural Sciences, Beijing 100081, China
    2. Institute of Forestry and Pomology, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100093, China

Received date: 2023-07-16

  Accepted date: 2023-08-02

  Online published: 2023-11-14

摘要

科学数据作为科学研究的有力工具和知识基础,其全流程的数据行为皆受研究者关注,数据重用作为其中关键的一环,对于科学数据管理共享使用发展具有举足轻重的意义。本文以中国农业科学院农业环境与可持续发展研究所农业环境数据共享服务平台为切入点,引出数据重用的相关研究,根据时间维度对科学数据数据重用定义的演变进行介绍,从数据重用影响框架的角度出发,分析科研人员、科学数据、数据平台三方面对数据重用的影响。探析较为流行与广泛使用的仓储型数据管理平台模式,结合农业数据共享服务平台的现状与问题,提出下一步发展启示。

本文引用格式

孙雨潇 , 李艳丽 , 李峰 , 李斌 . 数据重用影响因素对仓储型数据管理平台发展方向的启示[J]. 农业大数据学报, 2023 , 5(3) : 2 -10 . DOI: 10.19788/j.issn.2096-6369.230302

Abstract

As a powerful tool and knowledge foundation for scientific research, scientific data have attracted the attention of researchers throughout its entire process of data behavior. Data reuse, as a key component, is of great significance for the development of scientific data management and sharing. Taking the Agricultural Environment Data Sharing Service Platform, developed by the Institute of Agricultural Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, as the starting point, the article introduces relevant research on data reuse and the evolution of the definition of scientific data reuse in terms of time dimension. From the perspective of the impact framework of data reuse, it analyzes the impact of researchers, scientific data, and data platforms on data reuse. Moreover, the article explores the popular and widely-used warehouse-based data management platform models, and proposes the next development inspiration, regarding to the current situation and problems of agricultural data sharing service platforms.

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