国家科学数据中心管理模式的国际对比研究
收稿日期: 2019-09-22
网络出版日期: 2020-04-08
基金资助
国家科技基础条件平台专项课题(2017DDJIZZ08);国家留学基金资助项目(201804910116)
International Comparative Study on Management Mode of National Science Data Center
Received date: 2019-09-22
Online published: 2020-04-08
以美英等国家科学数据中心体系为对象，分析其发展历程、管理模式和评价方式。通过网络调研与文献分析法，梳理美英及中国的国家科学数据中心的建设历程，归纳并提出其管理模式及评价方式。通过不同国家科学数据中心的对比分析，提出科学数据中心的发展演化模式。在美国，国家级、领域级、资源节点级数据中心都存在且有秩序地逐级汇交，形成由“毛细血管向主动脉汇交”提供数据流的汇流模式；在英国，国家级、领域级数据中心已基本涉及科学数据所包含的主要领域，形成由“几大主动脉并行”提供数据流的并行模式，由国家级和领域级数据中心直接获取并提供数据；在我国，类似于汇流模式，由国家形成重点领域的国家科学数据中心，规范科学数据管理，统筹规划和建设本部门（本地区）科学数据中心，鼓励其向国家级数据中心汇交数据，推进相关领域科技资源向国家平台汇聚与整合。结合我国于2019年6月发布的国家科学数据中心调整名单，本文对国家科学数据中心的科学数据管理生态关系、引入国家科学数据中心后我国科学数据管理有可能面临的新模式进行了探讨并提出了建议；认为我国在构建科学数据生态促进大科学发展的过程中，国家科学数据中心将发挥重大作用，为我国科技在大数据时代的发展提供支撑。
黄铭瑞, 李国庆, 李静, 范湘涛 . 国家科学数据中心管理模式的国际对比研究[J]. 农业大数据学报, 2019 , 1(4) : 14 -29 . DOI: 10.19788/j.issn.2096-6369.190402
This paper presents models of the development, management, evolution of national science data center systems in the United States, the United Kingdom， and China. Our methods include network research and literature analysis to analyze the construction process, management mode and evaluation methods of these science data center sys‐ tems. In the United States, national data centers, domain-level data centers, and resource-node data centers exist and share data in an orderly manner, forming a data flow model from“the capillary to the aortic convergence.”In the United Kingdom, national level and field research data centers form a data flow model with“several parallel aortas”, in which data is directly obtained from the national and domain-level data centers. In China, similar to the US convergence model, national science data centers are established in key areas throughout the country to stan‐ dardize science data management and plan and build science data centers in the regions. The regional data cen‐ ters are encouraged to submit data to national data centers, thereby promoting the flow of scientific and technological resources from the relevant fields to the national platforms for convergence and integration. Our paper also considers the adjustment list released by the National Science Data Centers of China in June 2019, discussing the ecological correlation in scientific data management of National science data center and its science data management model relative to the new model that China's science data management may face. It is argued that the National Scientific Data Centers will play an important role in promoting the development of big science in China and provide support for the development of science and technology in the era of big data.
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