专题:科技信息资源管理学的理论探索与实践

科研数据基础设施建设框架及运行机制研究——以粤港澳大湾区国际科技创新中心为例

  • 杨秀财 ,
  • 张嘉家 ,
  • 宋昊阳 ,
  • 常红
展开
  • 1 中山大学信息管理学院, 广州 510006;
    2 仲恺农业工程学院马克思主义学院, 广州 510230
杨秀财,博士研究生;张嘉家,本科生;宋昊阳,副教授,博士,硕士生导师;常红,副教授,博士,通信作者,E-mail:changhong@zhku.edu.cn。

收稿日期: 2024-04-01

  修回日期: 2024-06-24

  网络出版日期: 2025-01-15

基金资助

本文系国家社会科学基金一般项目“‘基于科学的创新’驱动新兴技术生成的机理及其促进政策研究”(项目编号:17BGL031)研究成果之一。

Research on the Construction Framework and Operational Mechanism of Research Data Infrastructure: A Case Study of the Guangdong-Hong Kong-Macao Greater Bay Area International Science and Technology Innovation Center

  • Yang Xiucai ,
  • Zhang Jiajia ,
  • Song Haoyang ,
  • Chang Hong
Expand
  • 1 School of Information Management, Sun Yat-sen University, Guangzhou 510006;
    2 School of Marxism, Zhongkai University of Agriculture and Engineering, Guangzhou 510230

Received date: 2024-04-01

  Revised date: 2024-06-24

  Online published: 2025-01-15

Supported by

This work is supported by the National Social Science Fund of China project, titled “Research on the Mechanism of Emerging Technology Generation Driven by Scientific Innovation and Its Promotion Policies” (Grant No. 17BGL031).

摘要

[目的/意义] 通过分析科研数据基础设施(research data infrastructure, RDI)的发展历程和国外的成功实践,探讨RDI在国内尤其是在大湾区国际科技创新中心的应用与实践,以期提供对我国RDI理论研究和建设实践的参考和启示,进而促进我国科技信息资源的高效管理和利用。[方法/过程] 采用案例研究法,选取大湾区国际科技创新中心为案例,首先系统回顾RDI的发展背景及其在国外的应用实践,然后构建适用于大湾区的RDI建设框架,并分析其可持续运行的机制。[结果/结论] 大湾区国际科技创新中心的RDI建设框架覆盖数据收集、处理、发布和利用等关键环节,其可持续运行机制涵盖管理机制、动力机制、协同机制、保障机制和评价机制等多个方面。这一框架和机制的建立,不仅为大湾区乃至全国的RDI建设提供重要参考,还为我国科研数据管理、开放共享和科技创新提供有力支撑。未来,需进一步加强RDI的理论研究,完善RDI建设和运行的实践,以实现科研数据资源的最大化利用和科技创新能力的全面提升。

本文引用格式

杨秀财 , 张嘉家 , 宋昊阳 , 常红 . 科研数据基础设施建设框架及运行机制研究——以粤港澳大湾区国际科技创新中心为例[J]. 图书情报工作, 2025 , 69(1) : 36 -45 . DOI: 10.13266/j.issn.0252-3116.2025.01.004

Abstract

[Purpose/Significance] This study aims to analyze the development and successful international practices of Research Data Infrastructure (RDI) to explore its application and practice within China, especially in the Guangdong-Hong Kong-Macao Greater Bay Area International Science and Technology Innovation Center. The goal is to provide references and insights for China’s RDI theoretical research and construction practices, thereby promoting the efficient management and utilization of China’s scientific and technological information resources. [Method/Process] Using case study approach, this study took the Greater Bay Area International Science and Technology Innovation Center as a case. It first systematically reviewed the development background of RDI and its application practices abroad. Then, it constructed an RDI framework for the Greater Bay Area and analyzed its sustainable operation mechanisms. [Result/Conclusion] The RDI framework of the Greater Bay Area International Science and Technology Innovation Center encompasses key aspects such as data collection, processing, publishing, and utilization. Its sustainable operation mechanisms include management mechanisms, driving mechanisms, collaborative mechanisms, safeguarding mechanisms, and evaluation mechanisms. The establishment of this framework and mechanisms could provide significant reference for the Greater Bay Area and the whole country. It also provides a strong support for the management, open sharing, and technological innovation of research data in China. In the future, it is necessary to further strengthen the theoretical research and practices of RDI construction and operation to maximize the utilization of research data resources and comprehensively enhance China’s capability for scientific and technological innovation.

参考文献

[1] 邓仲华, 李志芳. 科学研究范式的演化——大数据时代的科学研究第四范式[J]. 情报资料工作, 2013(4): 19-23. (DENG Z H, LI Z F. The evolution of scientific research paradigm: the fourth paradigm of scientific research in the era of big data[J]. Information and documentation services, 2013(4): 19-23.)
[2] 科学数据共享调研组. 科学数据共享工程的总体框架[J]. 中国基础科学, 2003(1): 65-70. (Scientific data sharing research group . General framework for scientific data sharing projects[J]. China basic science, 2003(1): 65-70.)
[3] 中共中央国务院. 粤港澳大湾区发展规划纲要[EB/OL]. [2024-06-20]. https://www.gov.cn/zhengce/2019-02/18/content_5366593.htm#1. (CPC Central Committee and State Council. The outline of the plan for the development of the Guangdong-Hong Kong-Macao Greater Bay Area[EB/OL]. [2024-06-20]. https://www.gov.cn/zhengce/2019-02/18/content_5366593.htm#1.)
[4] Riding the wave-how Europe can gain from the rising tide of scientific data-final report of the high level expert group on scientific data[EB/OL]. [2024-06-20]. http://ec.europa.eu/information_society/newsroom/cf/document.cfm?action=display&doc_id=707.
[5] A surfboard for riding the wave-towards a four country action program on research data[EB/OL]. [2024-06-20]. http://repository.jisc.ac.uk/6200/1/KE_Surfboard_Riding_the_Wave_Screen.pdf.
[6] The evolving landscape of federated research data infrastructures[EB/OL]. [2024-06-20]. http://repository.jisc.ac.uk/6730/1/Knowledge_Exchange_The_Evolving_Landscape_of_Federated_Research_Data_Infrastructures_Nov_2017.pdf.
[7] EUDAT CDI - Data shared and preserved across borders and disciplines[EB/OL]. [2024-06-20]. https://www.eudat.eu/sites/default/files/CDI_Brochure_16_jan_2018_web.pdf.
[8] The Australian research data infrastructure strategy[EB/OL]. [2024-06-20]. https://docs.education.gov.au/system/files/doc/other/the_australian_research_data_infrastructure_strategy.pdf.
[9] FRAN B, ROSS W, JOHN W. Building global infrastructure for data sharing and exchange through the research data alliance[EB/OL]. [2024-06-20]. http://www.dlib.org/dlib/january14/01guest_editorial.print.html.
[10] 钱锦琳, 刘桂锋. 国外科研数据管理研究综述[J]. 情报理论与实践, 2017, 40(10): 130-134. (QIAN J L, LIU G F. A review of research data management abroad[J]. Information studies: theory & application, 2017, 40(10): 130-134.)
[11] 魏悦, 刘桂锋. 基于数据生命周期的国外高校科学数据管理与共享政策分析[J]. 情报杂志, 2017, 36(5): 153-158. (WEI Y, LIU G F. Analysis of research data management and sharing policy in foreign universities based on data lifecycle[J]. Journal of intelligence, 2017, 36(5): 153-158.)
[12] 司莉, 邢文明. 国外科学数据管理与共享政策调查及对我国的启示[J]. 情报资料工作, 2013(1): 61-66. (SI L, XING W M. Scientific data management and sharing policies in foreign countries: investigation and inspiration to us[J]. Information and documentation services, 2013(1): 61-66.)
[13] 顾立平. 科研模式变革中的数据管理服务:实现开放获取、开放数据、开放科学的途径[J]. 中国图书馆学报, 2018, 44(6): 43-58. (GU L P. Data management services in the transition of research model: an approach of implementing open access, open data and open science[J]. Journal of library science in China, 2018, 44(6): 43-58.)
[14] 王敬, 王彦兵. 国外科研数据基础设施研究及实践的调研与分析[J]. 情报资料工作, 2016(6): 99-104. (WANG J, WANG Y B. Investigation and analysis of foreign research data infrastructure research and practice[J]. Information and documentation services, 2016(6): 99-104.)
[15] 张丽丽, 温亮明, 石蕾, 等. 国内外科学数据管理与开放共享的最新进展[J]. 中国科学院院刊, 2018, 33(8): 774-782. (ZHANG L L, WEN L M, SHI L, et al. Progress in scientific data management and sharing [J]. Bulletin of Chinese Academy of Sciences, 2018, 33(8): 774-782.)
[16] 李立睿, 邓仲华. “互联网+”视角下的科学数据生态系统研究[J]. 图书与情报, 2016(2): 66-71. (LI L R, DENG Z H. Research on scientific data ecosystem from the perspective of “Internet+” [J]. Library & information, 2016(2): 66-71.)
[17] 丁宁, 马浩琴. 国外高校科学数据生命周期管理模型比较研究及借鉴[J]. 图书情报工作, 2013, 57(6): 18-22. (DING N, MA H Q. The comparative research and reference on the scientific data lifecycle management in foreign universities[J]. Library and information service, 2013, 57(6): 18-22.)
[18] 沈志宏, 张晓林, 黎建辉. OpenCSDB:关联数据在科学数据库中的应用研究[J]. 中国图书馆学报, 2012, 38(5): 17-26. (SHENG Z H, ZHANG X L, LI J H. OpenCSDB: application of linked data in scientific database[J]. Journal of library science in China, 2012, 38(5): 17-26.)
[19] 沈志宏, 刘筱敏, 郭学兵, 等. 关联数据发布流程与关键问题研究——以科技文献、科学数据发布为例[J]. 中国图书馆学报, 2013, 39(2): 53-62. (SHENG Z H, LIU Y M, GUO X B, et al. A research on publishing workflow and key issues of linked data: experience with publishing scientific literature and scientific data as linked data[J]. Journal of library science in China, 2013, 39(2): 53-62.)
[20] 黎建辉, 周园春, 胡良霖, 等. 中国科学院科学数据云建设与服务[J]. 大数据, 2016, 2(6): 3-13. (LI J H, ZHOU Y C, HU L L, et al. Scientific data cloud construction and service of Chinese Academy of Sciences[J]. Big data research, 2016, 2(6): 3-13.)
[21] 王明明, 王卷乐, 赵强, 等. ICPSR科学数据中心的建设经验与启示[J]. 中国科技资源导刊, 2017, 49(6): 100-107. (WANG M M, WANG J L, ZHAO Q, et al. Experiences and enlightenment of ICPSR scientific data center development[J]. China science & technology resources review, 2017, 49(6): 100-107.)
[22] 曾粤亮, 梁心怡, 徐琳琳, 等. 协同视角下科研数据知识库联盟运行策略研究——以加拿大FRDR平台为例[J]. 情报理论与实践, 2023, 46(1): 61-71. (ZENG Y L, LIANG X Y, XU L L, et al. Research on the operation strategies of research data repository alliance from the perspective of collaboration: take FRDR as an example[J]. Information studies: theory & application, 2023, 46(1): 61-71.)
[23] 都平平, 李雨珂, 陈越. 高校科研数据资产化存储及数据复用权益许可研究[J]. 图书情报工作, 2022, 66(3): 45-53. (DU P P, LI Y K, CHEN Y. Research on asset storage and data reuse rights license of scientific research data in colleges and universities[J]. Library and information service, 2022, 66(3): 45-53.)
[24] 刘桂锋, 阮冰颖, 苏文成. 科研人员视角下科学数据安全风险识别框架探究[J]. 图书馆建设, 2022(4): 81-91. (LIU G F,RUAN B Y, SU W C. Research on scientific data security risk identification framework from the perspective of scientific researchers[J]. Library development, 2022(4): 81-91.)
[25] 彭玉芳, 陈将浩, 何志强. 基于机器学习和深度学习的南海证据性数据抽取算法比较与应用[J]. 现代情报, 2022, 42(2): 55-69. (PENG Y F, CHEN J H, HE Z Q. Comparison and application of South China Sea evidence data extraction algorithms based on the machine learning and the deep learning [J]. Journal of modern information, 2022, 42(2): 55-69.)
[26] 孙红蕾, 马岩, 郑建明. 城市信息基础设施效率测评研究[J]. 图书馆论坛, 2017, 37(5): 1-9. (SUN H L, MA Y, ZHENG J M. Efficiency evaluation of urban information infrastructure [J]. Library tribune, 2017, 37(5): 1-9.)
文章导航

/