数据与计算发展前沿 ›› 2024, Vol. 6 ›› Issue (4): 3-21.

CSTR: 32002.14.jfdc.CN10-1649/TP.2024.04.001

doi: 10.11871/jfdc.issn.2096-742X.2024.04.001

• 专刊：面向国家科学数据中心的基础软件栈及系统 • 上一篇    下一篇

科学数据网络：概念、系统与应用

沈志宏1,*(),朱小杰1,王华进1,佟继周2,郭学兵3,吴慧4,敏玉芳5,吴林寰6   

  1. 1.中国科学院计算机网络信息中心，北京 100083
    2.中国科学院国家空间科学中心，北京 100190
    3.中国科学院地理科学与资源研究所，北京 100101
    4.中国科学院植物研究所，北京 100093
    5.中国科学院西北生态环境资源研究院，甘肃 兰州 730000
    6.中国科学院微生物研究所，北京 100101
  • 收稿日期:2024-02-02 出版日期:2024-08-20 发布日期:2024-08-20
  • 通讯作者: *沈志宏（E-mail: bluejoe@cnic.cn）
  • 作者简介:沈志宏，正高级工程师，博士生导师，现任中国科学院计算机网络信息中心大数据部主任、中国科学院科学数据总中心常务副主任，研究方向为大数据管理与处理、图数据库管理系统、分布式计算、语义网技术，目前主持国家重点研发计划项目“面向国家科学数据中心的基础软件栈及系统”、中国科学院网信专项项目“科学大数据工程（三期）”。
    本文主要承担工作为：提出论文总体思路，完成引言部分、第1、2、3、5节主要内容。
    SHEN Zhihong, Ph.D., professor, doctoral supervisor. He is the director of the Big Data Department of the Computer Network Information Center, CAS, and also the director of the General Data Center of CAS. His main research direction includes scientific big data management, graph database, distributed computing, and semantic web technologies. He currently leads the national key R&D program project “Fundamental Software Stack and Systems for National Science Data Centers” and the Informatization Plan of Chinese Academy of Sciences program “Scientific Big Data Engineering (Phase III).”
    In this paper, he is mainly responsible for developing the overall concept and structure of the paper, as well as completing the major content of the Introduction, Sections 1, 2, 3, and 5.
    E-mail: bluejoe@cnic.cn
  • 基金资助:
    国家重点研发计划项目“面向国家科学数据中心的基础软件栈及系统”(2021YFF0704200);中国科学院“十四五”网信专项工程建设项目“科学大数据工程（三期）”(CAS-WX2022GC-02)

Research Data Network: Concept, Systems and Applications

SHEN Zhihong1,*(),ZHU Xiaojie1,WANG Huajin1,TONG Jizhou2,GUO Xuebing3,WU Hui4,MIN Yufang5,WU Linhuan6   

  1. 1. Computer Network Information Center, Chinese Academy of Science, Beijing 100083
    2. National Space Science Center, Chinese Academy of Sciences, Beijing 100190
    3. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101
    4. Institute of Botany, Chinese Academy of Sciences, Beijing 100093
    5. Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000
    6. Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101
  • Received:2024-02-02 Online:2024-08-20 Published:2024-08-20

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摘要：

【应用背景】 科学数据具有分散化、差异化、孤岛化等典型特征，构建可打破各种孤岛、有效整合分布式科学数据资源的基础设施具有重要意义。【方法】 本文梳理了国内外类网络科学数据平台、技术与系统的进展，阐明了科学数据网络的概念、特征、功能与关键技术，并针对新型科研范式下科学数据的协作利用需求，提出并设计了科学数据协作网络RDCN。【结论】 科学数据网络可有效改善科学数据的分散化、差异化、孤岛化问题，RDCN在生物多样性研究、生态系统野外台站观测研究、多信使天文学研究等融合科学协作场景中将发挥重大的作用。

关键词: 科学数据, 融合科学, 类网络科学数据平台, 科学数据网络, 科学数据协作网络

Abstract:

[Background] Research data exhibits typical characteristics of being dispersed, heterogeneous, and siloed. It is of great significance to build infrastructures that can break down barriers between various isolated islands and effectively integrate distributed research data resources. [Methods] After reviewing the state of network-based research data platforms and technological systems, this paper explains the concept, characteristics, functions, and key technologies of the Research Data Network. To meet the collaborative needs of research data within the new research paradigm, this paper proposes RDCN as a collaboration-enabled research data network and introduces its design and implementation. [Results] The research data network can effectively address the issues of dispersed, heterogeneous, and siloed data. RDCN will play a significant role in research collaboration scenarios, such as biodiversity research, ecosystem field station observations, and multi-messenger astronomy research.

Key words: research data, convergence science, network-like research data platform, research data network, research data collaboration network