农业图书情报学报

• •    

日本科研数据云(RDC)进展及其启示

成帆1,2, 顾立平1,2()   

  1. 1. 中国科学院文献情报中心,北京 100190
    2. 中国科学院大学 经济与管理学院信息资源管理系,北京 100190
  • 收稿日期:2025-04-16 出版日期:2025-09-04
  • 通讯作者: 顾立平
  • 作者简介:

    成帆,博士研究生,副高级工程师,研究方向为数据科学、开放科学研究

  • 基金资助:
    国家社会科学一般项目“开放科学环境中数据馆员服务模式研究”(21BTQ005)

Research Data Cloud of Japan's Open Science Consortium

CHENG Fan1,2, GU Liping1,2()   

  1. 1. National Science Library, Chinese Academy of Sciences, Beijing 100190
    2. Department of Information Resource Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190
  • Received:2025-04-16 Online:2025-09-04
  • Contact: GU Liping

摘要:

【目的/意义】 聚焦日本科研数据云(RDC)体系的发展进程与服务机制,分析其在科研数据管理与开放共享中的关键作用,重点探讨其以小团队驱动大网络的协同发展模式,旨在为中国科研数据基础设施建设与开放科学发展推进提供借鉴。 【方法/过程】 采用案例研究法,系统梳理日本开放科学与数据平台研究中心(RCOS)支持的RDC项目在开放科学基础设施建设中的实践经验,重点分析其在数据治理、数据溯源、安全计算与存储、跨机构协作等方面的具体策略与技术创新。 【结果/结论】 日本在资源有限的背景下,通过资源整合与模块化平台建设,搭建面向科研人员、数据管理员、图书馆、产业界及公众的综合性科研数据生态系统。其灵活高效的组织模式、运行机制及政策支持,体现出以小团队、大网络的实践特色,为中国构建本土化、可持续的开放科学基础设施体系提供重要启示。

关键词: 开放科学, 日本政策, 科研数据平台, 数据治理, 国际合作

Abstract:

[Purpose/Significance] This paper focuses on the development process and service mechanisms of Japan's Research Data Cloud (RDC) system, a core national infrastructure coordinated by the Research Center for Open Science and Data Platform (RCOS). Against the backdrop of growing global attention to open science, RDC presents a practical model for integrating data management, open sharing, publication, search, and preservation throughout the research lifecycle. The paper highlights the unique collaborative model of RDC, which is characterized by a small team driving large networks. Compared to prior literature that often emphasizes technical architectures or isolated institutional efforts, the paper situates RDC within Japan's broader open science strategy, offering both theoretical and practical insights. It explores how RDC contributes to advancing the FAIR data principles, supporting cross-sector innovation, and strengthening national science and technology governance. The analysis also offers strategic lessons for China in building a sustainable and service-oriented research data system. [Method/Process] Using a qualitative case study approach, the paper draws on a combination of primary and secondary sources, including official reports, project documentation, and academic literature, and publicly available platform data related to the RDC initiative. It systematically analyzes the organizational structure and collaborative mechanisms of RDC, focusing on the institutional roles, platform components (GakuNin RDM, WEKO3, CiNii Research), and key technological innovations such as data governance, data provenance, secure computing, and trusted storage. In particular, it analyzes how RCOS functions as a neutral coordinator that bridges stakeholders across ministries, universities, and research organizations, and how it plays a role in translating policy mandates into technical services, integrating institutional workflows, and fostering community participation in the open science ecosystem. [Results/Conclusions] Despite constrained resources, RDC has developed a comprehensive research data ecosystem that serves researchers, data managers, librarians, industry, and the public. Japan's experience demonstrates that emphasizing interoperability, governance coordination, and capacity building, especially through small-scale research teams and nationwide collaborative networks, can effectively support the development of robust research infrastructure. The paper concludes by proposing several recommendations for China: the creation of independent coordination agencies to avoid fragmented development, the establishment of standardized service frameworks to enhance interoperability, and the implementation of tiered training programs to improve data literacy and management capacity across disciplines. Future research should further explore comparative institutional models, examine the long-term sustainability of open science ecosystems under different governance conditions, and investigate the cultural, legal, and technical dimensions that shape localized approaches to research data governance.

Key words: open science, Japanese policy, research data platform, data governance, international collaboration

中图分类号:  G250

引用本文

成帆, 顾立平. 日本科研数据云(RDC)进展及其启示[J/OL]. 农业图书情报学报. https://doi.org/10.13998/j.cnki.issn1002-1248.25-0315.

CHENG Fan, GU Liping. Research Data Cloud of Japan's Open Science Consortium[J/OL]. Journal of library and information science in agriculture. https://doi.org/10.13998/j.cnki.issn1002-1248.25-0315.