研究论文

科学数据价值评估研究

  • 赵一鸣 ,
  • 谭欣佩 ,
  • 张胜发
展开
  • 1 武汉大学信息资源研究中心 武汉 430072;
    2 武汉大学信息管理学院 武汉 430072;
    3 武汉大学大数据研究院 武汉 430072;
    4 武汉大学图书情报国家级实验教学示范中心 武汉 430072;
    5 中国医学科学院国家人口健康科学数据中心 北京 100020
赵一鸣,教授,博士,E-mail:zhaoyiming@whu.edu.cn;谭欣佩,硕士研究生;张胜发,助理研究员,博士。

收稿日期: 2024-04-24

  修回日期: 2024-08-20

  网络出版日期: 2025-03-18

基金资助

本文系国家自然科学基金面上项目“‘搜索即学习’视角下的用户学习状态感知与智能响应研究”(项目编号:72274146)和国家自然科学基金面上项目“探寻式搜索过程中的路径识别与评价研究”(项目编号:71874130)研究成果之一。

Research on Scientific Data Value Evaluation

  • Zhao Yiming ,
  • Tan Xinpei ,
  • Zhang Shengfa
Expand
  • 1 The Center for Studies of Information Resources, Wuhan University, Wuhan 430072;
    2 School of Information Management, Wuhan University, Wuhan 430072;
    3 Big Data Research Institute, Wuhan University, Wuhan 430072;
    4 National Demonstration Center for Experimental Library and Information Science Education, Wuhan 430072;
    5 National Population Health Data Center, National Science & Technology Infrastructure, Beijing 100020
Zhao Yiming,professor,PhD,E-mail:zhaoyiming@whu.edu.cn;Tan Xinpei,master candidate;Zhang Shengfa,assistant researcher,PhD.

Received date: 2024-04-24

  Revised date: 2024-08-20

  Online published: 2025-03-18

Supported by

This work is supported by the General Programs of the National Natural Science Foundation of China project, titled “Investigating the Awareness of Users’ Learning State and Intelligent Response from the Perspective of Search as Learning” (Grant No. 72274146) and “Identifying and Evaluating Search Trails in the Exploratory Search Process” (Grant No. 71874130).

摘要

[目的/意义] 科学数据是国家科技创新发展和经济社会发展的重要基础性战略资源,开展科学数据价值评估研究,对于激活科学数据价值、促进其价值提升、推动开放科学发展具有重要意义。[方法/过程] 以科学数据为研究对象,基于数据生命周期理论和价值提升理论,分析价值共创链路各节点主体对科学数据价值的影响,从基础价值、学术价值和开放共享价值3个维度构建科学数据价值评估体系,运用层次分析法获得指标权重。最后选取国家青藏高原科学数据中心的科学数据价值进行实验验证。[结果/结论] 提出的科学数据价值评估指标体系可以有效地综合评估科学数据的价值,同时能够为科学数据管理和开放共享,以及相关政策制定提供理论指导和实践依据,有助于推动科学数据的价值提升与高效利用,进而促进开放科学的发展。

本文引用格式

赵一鸣 , 谭欣佩 , 张胜发 . 科学数据价值评估研究[J]. 图书情报工作, 2025 , 69(6) : 58 -71 . DOI: 10.13266/j.issn.0252-3116.2025.06.005

Abstract

[Purpose/Significance] Scientific data serves as a pivotal strategic asset for driving national technological innovation and propelling socio-economic progress. Evaluating the value of scientific data is crucial for unlocking its potential, augmenting its utility, and fostering the advancement of open science. [Method/Process] Firstly, scientific data was taken as the research object. Based on theories of data lifecycle and value enhancement, the factors and mechanisms affecting scientific data value at each node in the value co-creation chain were analyzed. Secondly, a scientific data value evaluation system was constructed across three dimensions: fundamental value, academic value, and open-sharing value. The weights of various indicators were determined using the analytic hierarchy process (AHP). Finally, the evaluation system was validated through experiments with datasets from the National Tibetan Plateau Data Center. [Result/Conclusion] The proposed scientific data value evaluation system can effectively evaluate the value of scientific data and provides theoretical guidance and practical implications for the scientific data management, opening and sharing, and the development of related policies. This contributes to enhancing and efficiently utilizing the value of scientific data and advancing the development of open science.

参考文献

[1] 图书馆·情报与文献学名词审定委员会. 图书馆·情报与文献学名词[M]. 北京: 科学出版社, 2019: 92. (Library: terminology committee for information and documentation.Library, information and documentation terminology [M]. Beijing: Science Press, 2019: 92.)
[2] 冯媛. 科学数据开放共享的价值共创模型及运行机制研究[J]. 图书馆, 2022(9): 29-37. (FENG Y. Value co-creation model and operation mechanisms of open sharing of scientific data[J]. Library, 2022(9): 29-37.)
[3] 国务院办公厅. 国务院办公厅关于印发科学数据管理办法的通知[EB/OL]. [2024-12-03]. https://www.gov.cn/gongbao/content/2018/content_5283177.htm. (General Office of the State Council. Notice of the General Office of the State Council on the issuance of the measures for the management of scientific data[EB/OL]. [2024-12-03]. https://www.gov.cn/gongbao/content/2018/content_5283177.htm.)
[4] JUMPER J, EVANS R, PRITZEL A, et al. Highly accurate protein structure prediction with AlphaFold[J]. Nature, 2021, 596: 583-589.
[5] STUART D, BAYNES G, HRYNASZKIEWICZ I, et al. Whitepaper: practical challenges for researchers in data sharing[J]. Figshare, 2018: 5975011.v1.
[6] 马捷, 郝志远, 李丽华, 等. 数字化转型视域下的数据价值研究综述: 内涵阐述、作用机制、场景应用与数据创新[J]. 图书情报工作, 2023, 67(15): 4-13. (MA J, HAO Z Y, LI L H, et al. A review of data value research from the perspective of digital transformation: connotation description, mechanism, scenario applicationand data innovation[J]. Library and information service, 2023, 67(15): 4-13.)
[7] 王丹丹, 刘亚宁. 科学数据价值: 研究述评与展望[J]. 图书情报工作, 2023, 67(9): 141-150. (WANG D D, LIU Y N. The value of scientific data: research review and prospect[J]. Library and information service, 2023, 67(9): 141-150.)
[8] 黄国彬, 郑霞. 数据论文的内容规范性研究[J]. 图书情报工作, 2019, 63(22): 129-140. (HUANG G B, ZHENG X. Research on content normalization of data paper[J]. Library and information service, 2019, 63(22): 129-140.)
[9] 江洪, 钟永恒. 国际科学数据共享研究[J]. 现代情报, 2008(11): 56-58. (JIANG H, ZHONG Y H. Study of the international scientific data sharing[J]. Journal of modern information, 2008(11): 56-58.)
[10] 刘闯, 张应华. 全球变化暨地球科学数据影响力分区方法及2019年实践研究[J]. 全球变化数据学报(中英文), 2019, 3(3): 207-226, 317-336. (LIU C, ZHANG Y H. Methodology and practice on quantifying the impact of global change & earth system science data in 2019[J]. Journal of global change data & discovery, 2019, 3(3): 207-226, 317-336.)
[11] 丁楠, 黎娇, 李文雨泽, 等. 基于引用的科学数据评价研究[J]. 图书与情报, 2014(5): 95-99. (DING N, LI J, LI W Y Z, et al. Scientific data evaluation based on data citation[J]. Library and information, 2014(5): 95-99.)
[12] 王雪, 马胜利, 佘曾溧, 等. 科学数据的引用行为及其影响力研究[J]. 情报学报, 2016, 35(11): 1132-1139. (WANG X, MA S L, SHE Z L, et al. Research on citation behavior of scientific data andc its influence[J]. Journal of the China Society for Scientific and Technical Information, 2016, 35(11): 1132-1139.)
[13] 涂志芳, 刘兹恒. 国内外科学数据管理服务评价研究与实践进展[J]. 图书馆建设, 2021(2): 108-117. (TU Z F, LIU Z H. Advances in evaluation of research data management services at home and abroad: research and practice[J]. Library development, 2021(2): 108-117.)
[14] 何思源. 科学数据价值鉴定策略研究[J]. 档案与建设, 2024(1): 64-70. (HE S Y. Research on strategies for value appraisal of scientific data[J]. Archives & construction, 2024(1): 64-70.)
[15] PRIEM J, HEMMINGER B H. Scientometrics 2.0:new metrics of scholarly impact on the social Web [J]. First monday, 2010, 15(7): 379-382.
[16] 郭倩影, 赵丹群. 基于Altmetrics的学术论文评价研究评述[J]. 情报理论与实践, 2021, 44(9): 190-197. (GUO Q Y, ZHAO D Q. Review of academic paper evaluation based on altmetrics.Information studies: theory & application, 2021, 44(9): 190-197.)
[17] PRIEM J, COSTELLO K L. How and why scholars cite on Twitter[J]. Proceedings of the American Society for Information Science and Technology, 2010, 47(1): 1-4.
[18] 李龙飞, 余厚强, 尹梓涵, 等. 替代计量学视角下科学数据集价值的定量测度研究[J]. 情报理论与实践, 2020, 43(9): 47-52, 71. (LI L F, YU H Q, YIN Z H, et al. Quantitative measure of the value of scientific datasets from perspective of altmetrics[J]. Information studies: theory & application, 2020, 43(9): 47-52, 71.)
[19] 任颖, 李楠. 科学数据价值共创系统构建及仿真分析[J]. 数字图书馆论坛, 2023, 19(5): 42-53. (REN Y, LI N. Construction and simulation analysis of scientific data value co-creation system[J]. Digital library forum, 2023, 19(5): 42-53.)
[20] 金银实. 科学数据共享价值共创机理及实现策略研究[D]. 长春: 东北师范大学, 2023. (JIN Y S. Research on value co-creation mechanism and realization strategy of scientific data sharing[D]. Changchun: Northeast Normal University, 2023.)
[21] 盛小平, 吴红. 科学数据开放共享活动中不同利益相关者动力分析[J]. 图书情报工作, 2019, 63(17): 40-50. (SHENG X P, WU H. An analysis of different stakeholders’ motivations in open sharing of scientific data[J]. Library and information service, 2019, 63(17): 40-50.)
[22] MILLER H G, MORK P. From data to decisions: a value chain for big data [J]. IT professional, 2013, 15(1): 57-59.
[23] 孙俐丽, 盛杰霏. 开放科学数据价值共创主体的共生模式研究[J]. 现代情报, 2024, 44(3): 120-130. (SUN L L, SHENG J F. Research on the yymbiosis model of open scientific data value co-creation subjects[J]. Journal of modern information, 2024, 44(3): 120-130.)
[24] 马素素. 高校图书馆嵌入式科学数据服务模式构建研究[D]. 曲阜: 曲阜师范大学, 2023. (MA S S. Rearch on the service mode of embedded scientific data service in university library[D]. Qufu: Qufu Normal University, 2023.)
[25] 顾立平, 陈新兰, 张潇月, 等. 开放科研数据中的数据价值提升策略[J]. 图书馆论坛, 2020, 40(9): 115-124. (GU L P, CHEN X L, ZHANG X Y, et al. A strategy for enhancing the value of open research data[J]. Library tribune, 2020, 40(9): 115-124.)
[26] 孙九林. 科学数据资源与共享[J]. 中国基础科学, 2003(1): 30-33. (SUN J L. Scientific data resources and sharing[J]. China Basic Science, 2003(1): 30-33.)
[27] 董诚, 侯敏. 科技资源共享价值最大化的三层次模型(VAA)[J]. 科技管理研究, 2013, 33(11): 231-234. (DONG C, HOU M. A three-layered model that sharing maximizes the value of scientific and technical resources (VAA)[J]. Science and technology management research, 2013, 33(11): 231-234.)
[28] 邓君, 贾晓青, 马晓君, 等. 科学数据价值鉴定标准研究[J]. 情报科学, 2013, 31(9): 37-41. (DENG J, JIA X Q, MA X J, et al. Study in appraisal exandard of scientific data value[J]. Information science, 2013, 31(9): 37-41.)
[29] 武琳, 马丽玉. 开放数据价值提升的关键——数据服务机构[J]. 情报资料工作, 2023, 44(4): 105-112. (WU L, MA L Y. The key to improving the value of open data: data service institutions[J]. Information and documentation services, 2023, 44(4): 105-112.)
[30] PRAHALAD C K, RAMASWAMY V. Co-creation experiences:the next practice in value creation[J]. Journal of interactive marketing, 2004, 18(3): 5-14.
[31] ZONG W, LIN S, GAO Y, et al. Process-driven quality improvement for scientific data based on information product map[J]. The electronic library, 2022, 40(3): 177-195.
[32] 高艳云. 中美CPI数据质量的比较分析:基于国际货币基金组织的DQAF框架[J]. 统计研究, 2008(11): 51-56. (GAO Y Y. Comparison on data quality of CPI between China and United States based on IMF’s DQAF[J]. Statistical research, 2008(11): 51-56.)
[33] 尚渡新, 刘桂锋, 王婧怡, 等. 基于关联数据的科学数据与期刊论文互联机制研究[J]. 情报理论与实践, 2023, 46(5): 166-175. (SHANG D X, LIU G F, WANG J Y, et al. Research and implementation of scientific data and journal articles interconnection based on linked data[J]. Information studies: theory & application, 2023, 46(5): 166-175.)
[34] 许鑫, 叶丁菱. 多维影响力融合视域下的数据论文评价研究[J]. 情报学报, 2022, 41(3): 275-286. (XU X, YE D L. Evaluation of data papers from the perspective of multi-dimensional influence fusion[J]. Journal of the China Society for Scientific and Technical Information, 2022, 41(3): 275-286.)
[35] 刘闯.数据影响力积分(DIS)——数据影响力新的计量方法[J]. 全球变化数据学报, 2018, 2(2): 135-143. (LIU C. Data impact score (DIS): a quantitative method of data performance to the data-driven sciences[J]. Journal of global change data & discovery, 2018, 2(2): 135-143.)
[36] PIWOWAR H. Value all research products[J]. Nature, 2013, 493(7431): 159.
[37] 秦奋, 高健. 基于Scopus数据库的Altmetrics指标与引文计量对比分析[J]. 情报学报, 2019, 38(4): 377-383. (QIN F, GAO J.Comparative analysis of altmetrics and citation measurement based on the scopus database[J]. Journal of the China Society for Scientific and Technical Information, 2019, 38(4): 377-383.)
[38] 邢文明, 郭安琪, 秦顺, 等. 科学数据管理与共享的FAIR原则——背景、内容与实施[J]. 信息资源管理学报, 2021, 11(2): 60-68, 84. (XING W M, GUO A Q, QIN S, et al. FAIR Principle of scientific data management and sharing: background, content and implementation[J]. Journal of information resources management, 2021, 11(2): 60-68, 84.)
[39] WILKINSON M D, DUMONTIER M, AALBERSBERG I J, et al. The FAIR guiding principles for scientific data management and stewardship[J]. Scientific data, 2016, 3: 160018.
[40] 刘智锋, 王继民, 李倩. 元数据质量评价研究综述[J]. 情报理论与实践, 2022, 45(7): 42-48. (LIU Z F, WANG J M, LI Q. A survey of research on metadata quality evaluation[J]. Information studies: theory & application, 2022, 45(7): 42-48.)
[41] SCHMIDT B, GEMEINHOLZER B, TRELOAR A.Open data in global environmental research:the belmont forum’s open data survey[J]. PLoS one, 2016, 11(1): e0146695. https://doi.org/10.1371/journal.pone.0146695.
[42] UNESCO recommendation on open science[EB/OL]. [2024-12-03]. https://unesdoc.unesco.org/ark:/48223/pf0000379949.locale=en.
[43] 潘小多, 李新, 冉有华, 等. 开放科学背景下的科学数据开放共享:国家青藏高原科学数据中心的实践[J]. 大数据, 2022(1): 113-120. (PAN X D, LI X, RAN Y H, et al. Open access of scientific data in the context of open science: the practice of the National Tibetan Plateau Data Center[J]. Big data research, 2022(1): 113-120.)
[44] BUDRONI P, CLAUDEBURGEMAN J, SCHOUPPE M, et al. Architectures of knowledge:the European open science cloud[J]. ABI technik, 2019, 39(2): 130-141.
[45] 宋佳, 温亮明, 李洋. 科学数据共享FAIR原则: 背景、内容及实践[J]. 情报资料工作, 2021, 42(1): 57-68. (SONG J, WEN L M, LI Y. Scientific data sharing FAIR data principles: background, content and practice[J]. Information and documentation services, 2021, 42(1): 57-68.)
[46] 郭金玉, 张忠彬, 孙庆云. 层次分析法的研究与应用[J]. 中国安全科学学报, 2008(5): 148-153. (GUO J Y, ZHANG Z B, SUN Q Y. Study and aplications of analytic hierarchy proces[J]. China safety science journal, 2008(5): 148-153.)
[47] 丰佰恒, 杜宝贵. 大模型视域下大数据政策生态链研究——以科学数据政策为例[J/OL]. 现代情报, 1-16[2024-12-19]. http://kns.cnki.net/kcms/detail/22.1182.G3.20240514.1010.002.html. (FENG B H, DU B G. Research on the ecological chain of big data policy from the perspective of big model: a case study of science data policy[J]. Journal of modern information, 1-16[2024-12-19]. http://kns.cnki.net/kcms/detail/22.1182.G3.20240514.1010.002.html.)
[48] 薛德军, 师庆辉, 毕琰虹, 等. 数据引擎驱动的学术出版大模型——实测检验大规模高质量数据在构建高性能模型中的核心地位[J]. 数字出版研究, 2024, 3(3): 122-132. (XUE D J, SHI Q H, BI Y H, et al. Data-driven academic publishing large model: an empirical test of centrality of large-scale and high-quality data in building high-performance models[J]. Digital publishing research, 2024, 3(3): 122-132.)
[49] BROWN T B, MANN B, RYDER N, et al. Language models are few-shot learners[J]. Advances in neural information processing systems, 2020, 33: 1877-1901.
[50] LIU Y, CAO J, LIU C, et al. Datasets for large language models: A comprehensive survey[EB/OL]. [2024-12-20]. https://arxiv.org/pdf/2402.18041.
[51] 王翠萍, 宋雯琪, 姜鑫妍, 等. 我国科学数据共享平台数据描述及引用规范调查研究[J]. 图书馆学研究, 2022(11): 76-85. (WANG C P, SONG W Q, JIANG X Y, et al. Investigation and research on scientifc data description and citation standards of domestic scientifc data sharing platform[J]. Research on library science, 2022(11): 76-85.)
文章导航

/

〈 〉