研究综述

农业生物多样性大数据平台建设研究和展望

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  • 1.中国科学院文献情报中心 资源建设与知识组织中心,北京 100190
    2.中国科学院植物研究所 植被与环境变化重点实验室,北京 100093
    3.中国科学院文献情报中心 学术期刊动态语义出版与知识服务实验室,北京 100190
许哲平,男,博士,研究方向:科学数据管理与应用、生物多样性信息学;E-mail: xuzp@mail.las.ac.cn

收稿日期: 2019-04-06

  网络出版日期: 2019-08-21

基金资助

中国科学院A类战略性先导科技专项(XDA19050000);中国科学院文献情报领域引进优秀人才计划

Big Data Portal Development in Agrobiodiversity: Current Research and Future Outlooks

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  • 1.Department of Collection & Knowledge Organization Center, National Science Library, Chinese Academy of Sciences, Beijing 100190
    2.State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093
    3.Laboratory of Dynamic Semantic Publishing of Academic Journal and Knowledge Service, National Science Library, Chinese Academy of Sciences, Beijing 100190

Received date: 2019-04-06

  Online published: 2019-08-21

摘要

农业生物多样性是指直接或间接用于粮食和农业的动物、植物和微生物的多样性和变异性,包括作物、家畜、林业和渔业等。它位于整个农业系统的底层,是农业生产信息化的重要内容,也是国家战略资源和国家安全的重要基础。国内外相关组织机构和项目积累了很多的资源和建设经验,但是仍然存在资源零散分布、缺乏顶层设计、元数据标准规范应用不足、平台之间的数据交互不够、数据的快速实时响应比较困难、高端农业智库及其资源平台建设薄弱等问题。为了更好地推动我国农业生物多样性大数据平台的研究和开发工作,本文着重从科学数据平台(基础数据平台、作物数据平台、家畜数据平台、林业数据平台、渔业数据平台、传统文化知识平台、智库平台和评估指标)和相关信息化基础资源对象(术语库、主题词表、元数据标准规范、本体和科研工作流)来梳理农业生物多样性大数据的国内外研究和应用进展,并从基础层、资源层、组织层和应用服务层等四个层次来提出农业生物多样性大数据平台的顶层建设框架,还针对当前现状和问题提出了建议和展望,为我国农业生物多样性大数据平台建设和资源共享服务提供参考。

本文引用格式

许哲平,邵曾婷,朱学军,王昉,王媛媛,肖曼,马克平 . 农业生物多样性大数据平台建设研究和展望[J]. 农业大数据学报, 2019 , 1(2) : 76 -87 . DOI: 10.19788/j.issn.2096-6369.190207

Abstract

Agrobiodiversity refers to the variety and variability of animals, plants, and microorganisms used directly or indirectly for food and agriculture, including crops, livestock, forestry, and fisheries. The underpinning of the entire agricultural system and an important part of agricultural production informatization, agrobiodiversity is also the basis of national resource strategies and national security. Although data and knowledge related to agrobiodiversity have been obtained from various research projects, several problems still exist; these include scattered data, lack of top-level designs, inadequate data standards, insufficiently interoperable systems, slow response, and few high-quality think tanks and data portals. To improve research and development on a big data portal for agrobiodiversity in China, we describe advances in agrobiodiversity big data in China and abroad in terms of research data platforms (basic, crop, livestock, forestry, and fishery data platforms; traditional cultural knowledge and think tank platforms; and assessment indicators) and basic resource objects (taxonomy, thesaurus, metadata standard, ontology, and scientific research workflow). In addition, we suggest a system architecture comprising four levels, namely, basic, resource, organizational, and application levels. Finally, we provide a future outlook on the construction and resource sharing of agrobiodiversity data platforms in China.

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