基于规则的科学数据安全治理框架：理解数据“保护-利用”失衡及挑战的新工具

doi:10.19788/j.issn.2096-6369.000068

农业大数据学报 ›› 2024, Vol. 6 ›› Issue (3): 295-306.doi: 10.19788/j.issn.2096-6369.000068

• “面向高质量共享的科学数据安全”专刊（下） • 下一篇

基于规则的科学数据安全治理框架：理解数据“保护-利用”失衡及挑战的新工具

王健¹^,⁴^,⁶(), 周国民²^,⁴^,⁶, 廖方宇³, 许哲平⁵^,⁷, 张建华¹^,⁴^,⁶^,^*(), 刘婷婷¹^,⁴

1.中国农业科学院农业信息研究所，北京 100081
2.农业农村部南京农业机械化研究所，南京 210014
3.中国科学院计算机网络信息中心，北京 100083
4.国家农业科学数据中心，北京 100081
5.中国科学院文献信息中心，北京 100190
6.中国农业科学院国家南繁研究院，海南三亚 572024
7.中国科学院大学经济管理学院，北京 100190

收稿日期:2024-06-08 接受日期:2024-09-24 出版日期:2024-09-26 发布日期:2024-10-01
通讯作者: 张建华，E-mail：zhangjianhua@caas.cn。
作者简介:王健，E-mail：wangjian01@caas.cn。
基金资助:
国家科技基础条件平台中心委托课题“数据流动政策对科学数据管理与应用影响研究”;中央级公益性科研院所基本科研业务费专项(JBYW-AII-2024-05);中央级公益性科研院所基本科研业务费专项(JBYW-AII-2023-06);中国农业科学院科技创新工程(CAAS-ASTIP-2024-AII);中国农业科学院科技创新工程(CAAS-ASTIP-2023-AII)

Rule-Based Framework for Scientific Data Security Governance: A New Tool for Understanding the Imbalance and Challenges of Data Protection and Utilization

WANG Jian¹^,⁴^,⁶(), ZHOU GuoMin²^,⁴^,⁶, LIAO FangYu³, XU ZhePing⁵^,⁷, ZHANG JianHua¹^,⁴^,⁶^,^*(), LIU TingTing¹^,⁴

1. The Agricultural Information Institute of CAAS, Beijing 100081, China
2. Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China
3. Computer Network Information Center of CAS, Beijing 100083, China
4. National Agricultural Scientific Data Center, Beijing 100081, China
5. National Sciences Library of Chinese Academy of Science, Beijing 100190, China
6. Hainan National Breeding and Multiplication Institute at Sanya, Chinese Academy of Agricultural Sciences, Sanya 572024, Hainan, China
7. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China

Received:2024-06-08 Accepted:2024-09-24 Published:2024-09-26 Online:2024-10-01

摘要/Abstract

摘要：

随着全球数据安全法律法规愈发关注隐私保护，以及数据主权、科技竞争和地缘政治等新型治理因素的影响，科学数据的“保护”要求不断提高。这种趋势在一定程度上抑制了数据采集、处理、传输和分析等“利用”功能，并对既有科学数据的“保护-利用”平衡产生了负面影响。目前，这种失衡趋势表现为法律合规负担过重以及公共科学数据可用性逐渐减弱等治理挑战，现有研究和实践缺乏必要的分析工具来全面、系统地理解并应对这些挑战。为填补这一空白，论文提出了一个基于规则的科学数据安全治理框架，旨在从法律法规、伦理规范和机构政策等安全治理规则的角度系统分析“保护-利用”失衡及相关挑战。该框架整合了主要的科学数据安全治理规则类型，并结合“岛桥模型”、“法律-伦理”均衡和“适度落实”原则等三项分析工具，构建了治理规则与“保护-利用”平衡之间的传导路径。通过这一框架，论文解释并初步验证了其在理解科学数据合规责任过重和公共科学数据可用性弱化两大挑战中的应用价值。在全球科学数据安全法规日趋严苛的背景下，本文提出的基于规则的分析视角及相关工具，丰富了科学数据安全治理的理论基础，并为学术界、数据管理者和政策制定者提供了应对当前挑战的有效工具和政策沟通的理论支撑。这一框架为未来在数据安全治理中的应用和扩展提供了重要参考，也为保障科学数据的可持续利用提供了关键指导。

关键词: 科学数据治理, 科学数据安全, 科学数据共享, 科学数据伦理, 数据“保护-利用”平衡

Abstract:

With the implementation of various data security laws and regulations centered on privacy protection, and the emergence of new governance factors such as data sovereignty, technological competition, and geopolitics, the requirements for the "protection" of scientific data have been increasingly elevated. This has objectively suppressed the "utilization" functions of data collection, processing, transmission, and analysis, leading to a significant risk of imbalance between the protection and utilization of scientific data. This imbalance is externally manifested in challenges such as the excessive burden of legal compliance and the weakening availability of public scientific data. The academic community, data managers, and policymakers urgently need effective analytical tools to understand and address these challenges in a systematic way. In response to this gap, this paper proposes a rule-based governance framework for scientific data security, aiming to provide a systematic analytical tool to address the protection-utilization imbalance and related challenges from the perspective of governance rules, including laws, ethics, and institutional policies. This framework integrates the major rule types in scientific data security governance and introduces three analytical tools: the "Island-Bridge Model," the "Law-Ethics Balance," and the "Moderate Implementation" principle, to explain the interaction mechanisms of these rules. The framework establishes the transmission paths between governance rules and the protection-utilization balance and uses these tools to explain two key challenges—excessive compliance burdens and weakened public scientific data availability—demonstrating its explanatory power and practical value. In the context of the long-term tightening of data security regulations, the rule-based analytical perspective and tools proposed in this paper enrich the theoretical foundation of scientific data security governance and provide practical references for addressing these challenges. The framework also offers essential theoretical support for policy communication among the academic community, data managers, and policymakers, ensuring the sustainable utilization of scientific data in the future.

Key words: scientific data governance, scientific data protection, scientific data sharing, scientific data ethics, protection-utilization balance of data

王健, 周国民, 廖方宇, 许哲平, 张建华, 刘婷婷. 基于规则的科学数据安全治理框架：理解数据“保护-利用”失衡及挑战的新工具[J]. 农业大数据学报, 2024, 6(3): 295-306.

WANG Jian, ZHOU GuoMin, LIAO FangYu, XU ZhePing, ZHANG JianHua, LIU TingTing. Rule-Based Framework for Scientific Data Security Governance: A New Tool for Understanding the Imbalance and Challenges of Data Protection and Utilization[J]. Journal of Agricultural Big Data, 2024, 6(3): 295-306.

图/表 2

参考文献 75

[1]	GAETA M C. Hard law and soft law on data protection: What a DPO should know to better perform his or her tasks[J/OL]. European Journal of Privacy Law & Technologies, 2019/2:61-78.
[2]	LI S C, CHEN Y W, HUANG Y. Examining compliance with personal data protection regulations in interorganizational data analysis[J/OL]. Sustainability, 2021, 13(20): 11459. DOI:10.3390/su132011459.
[3]	RUBINSTEIN I S, HARTZOG W. Anonymization and risk[J]. Washington Law Review, 2016, 91(2): 703-760.
[4]	郭华东. 专刊导读:把握“保护-利用”动态平衡,推进科学数据高质量发展[J]. 农业大数据学报, 2024, 6(2): 145. DOI:10.19788/j.issn.2096-6369.200003.
[5]	廖方宇, 李婧. 开放科学背景下科学数据开放共享安全挑战及我国对策思考[J]. 农业大数据学报, 2024, 6(2): 146-155. DOI:10.19788/j.issn.2096-6369.000027.
[6]	YAO K, PARK M K. Strengthening Data Governance for Effective Use of Open Data and Big Data Analytics for Combating COVID-19[M/OL]// UN Department of Economic and Social Affairs Policy Briefs NO89, 2020. https://desapublications.un.org/policy-briefs/undesa-policy-brief-89-strengthening-data-governance-effective-use-open-data-and-big.
[7]	VOIGT P, VON DEM BUSSCHE A. The EU General Data Protection Regulation (GDPR): A practical guide[M]. Springer International Publishing, 2017.
[8]	ALL EUROPEAN ACADEMIES, EUROPEAN ACADEMIES SCIENCE ADVISORY COUNCIL, FEDERATION OF EUROPEAN ACADEMIES OF MEDICINE. International Sharing of Personal Health Data for Research[M/OL]. 2021. DOI: https://doi.org/10.26356/IHDT.
[9]	DE HERT P, PAPAKONSTANTINOU V. The new general data protection regulation: Still a sound system for the protection of individuals?[J]. Computer Law & Security Review, 2012, 28(2): 130-142.
[10]	BORGMAN C L. Big Data, Little Data, No Data: Scholarship in the Networked World[M]. MIT Press, 2015.
[11]	KAYE J, WHITLEY E A, LUND D, et al. Dynamic consent: a patient interface for twenty-first century research networks[J]. European Journal of Human Genetics, 2015, 23(2): 141-146. doi: 10.1038/ejhg.2014.71 pmid: 24801761
[12]	GARRIDO S, FELLOWS L. The impact of data protection regulations on research: Balancing data sharing and privacy concerns[J]. Journal of Law, Medicine & Ethics, 2016, 44(1): 127-141.
[13]	PHILLIPS M, DOVE E S, KNOPPERS B M. A population data perspective on the regulation of health research[J]. Journal of Law and the Biosciences, 2017, 4(1): 27-46.
[14]	STAHL B C, RAINEY S, SHAW M. Challenges and opportunities of data governance in research: A critical perspective[J]. Science and Public Policy, 2021, 48(3): 395-407.
[15]	CONTRERAS J L. Bermuda’s legacy: Patents, policy and the design of the genome commons[J]. Minnesota Journal of Law, Science & Technology, 2011, 12(1): 61-125.
[16]	EDWARDS J L. Research and societal benefits of the global biodiversity information facility[J/OL]. BioScience, 2004, 54(6):485-486. https://doi.org/10.1641/0006-3568(2004)054[0486:RASBOT]2.0.CO;2.
[17]	PISANI E, AABY P, BREUGELMANS J G, et al. Beyond open data: realizing the health benefits of sharing data[J]. BMJ, 2016, 355:i5295. https://doi.org/10.1136/bmj.i5295.
[18]	A Preliminary Opinion on data protection and scientific research[M/OL]. European Data Protection Supervisor, 2020. https://www.edps.europa.eu/sites/default/files/publication/20-01-06_opinion_research_en.pdf.
[19]	SCHWARTZ P M, SOLOVE D J. Reconciling personal information in the United States and European Union[J]. California Law Review, 2014, 102(4): 877-916.
[20]	BENDER A. The invalidation of the EU-U.S. safe harbor agreement: Implications for transatlantic data flows[J]. German Law Journal, 2016, 17(6): 1267-1282.
[21]	HOWISON M, ANGELL M, HASTINGS J S. Protecting sensitive data with secure data enclaves[J/OL]. Digital Government: Research and Practice, 2024, 5(2): 1-11. DOI:10.1145/3643686.
[22]	SABERI S, KOUHIZADEH M, SARKIS J, et al. Blockchain technology and its relationships to sustainable supply chain management[J/OL]. International Journal of Production Research, 2019, 57(7): 2117-2135. https://doi.org/10.1080/00207543.2018.1533261.
[23]	龚海燕, 李晓刚. 区块链与机密计算技术在材料数据库平台中的应用分析[J]. 农业大数据学报, 2024, 6(2): 241-252. DOI:10.19788/j.issn.2096-6369.000026.
[24]	陈纯, 任奎, 杨小虎, 等. 区块链与科学数据治理[J]. 科学通报, 2024, 69(9): 1137-1141.
[25]	ZWITTER A, GSTREIN O J. Big data, privacy, and COVID-19— learning from humanitarian expertise in data protection[J]. Journal of International Humanitarian Action, 2020, 5(1): 1-8.
[26]	FOSTER C, JACOB T. The impacts of data localization on privacy, security, and innovation[J]. Journal of Cyber Policy, 2018, 3(3): 365-384.
[27]	李宜展, 李泽霞. 国际科技组织与国际科技合作计划中的科学数据安全治理[J]. 农业大数据学报, 2024, 6(2): 161. DOI:10.19788/j.issn.2096-6369.000031.
[28]	CHANDER A, SUN H. Data SOVEREIGNTY: From the Digital Silk Road to the Return of the State[M/OL]. New York: Oxford University Press, 2023. https://academic.oup.com/book/55328.
[29]	宁宣凤, 吴涵, 付昊, 等. “数据主权”浪潮下企业如何构建全球数据管理体系 ——兼评美国《国家安全与个人数据保护法》提案[EB/OL]. https://www.chinalawinsight.com/2019/11/articles/cyber-security/数据主权浪潮下企业如何构建全球数据管理体系/.
[30]	黄海瑛, 何梦婷, 冉从敬. 数据主权安全风险的国际治理体系与我国路径研究[J]. 图书与情报, 2021(4): 15-28.
[31]	KOUPER I, RAYMOND A H, GIROUX S. An exploratory study of research data governance in the U.S.[J/OL]. Open Information Science, 2020, 4(1): 122-142. DOI:10.1515/opis-2020-0010.
[32]	MAHANTI R. Data Governance Success: Growing and Sustaining Data Governance[M/OL]. Singapore: Springer Singapore, 2021. https://link.springer.com/10.1007/978-981-16-5086-4.
[33]	HINKLE O. The Evolution of Data Governance[EB/OL]. (2020-05-18). https://www.dataversity.net/the-evolution-of-data-governance/.
[34]	AL-RUITHE M, BENKHELIFA E, HAMEED K. A systematic literature review of data governance and cloud data governance[J/OL]. Personal and Ubiquitous Computing, 2019, 23(5-6): 839-859. DOI:10.1007/s00779-017-1104-3.
[35]	LADLEY J. Data Governance: How to Design, Deploy, and Sustain an Effective Data Governance Program[M/OL]. Elsevier Science, 2019. https://books.google.com.sg/books?id=AkW9DwAAQBAJ.
[36]	SARSFIELD S. The Data Governance Imperative[M/OL]. IT Governance Publishing, 2009. https://www.jstor.org/stable/j.ctt5hh6sb.
[37]	MARCUCCI S, ALARCÓN N G, VERHULST S G, et al. Informing the Global Data Future: Benchmarking Data Governance Frameworks[J/OL]. Data & Policy, 2023, 5: e30. DOI:10.1017/dap.2023.24.
[38]	HENDERSON D, EARLEY S, DATA ADMINISTRATION MANAGEMENT ASSOCIATION. DAMA-DMBOK: data management body of knowledge[M].Second edition. Basking Ridge, New Jersey: Technics Publications, 2017.
[39]	FOTHERGILL B T, KNIGHT W, STAHL B C, et al. Responsible data governance of neuroscience big data[J/OL]. Frontiers in Neuro-informatics, 2019, 13:28. https://doi.org/10.3389/fninf.2019.00028.
[40]	AL-RUITHE M, BENKHELIFA E, HAMEED K. Data governance taxonomy: Cloud versus non-cloud[J/OL]. Sustainability, 2018, 10(1): 95. https://doi.org/10.3390/su10010095.
[41]	刘桂锋, 钱锦琳, 卢章平. 国内外数据治理研究进展:内涵,要素,模型与框架[J]. 图书情报工作, 2017, 61(21): 8.
[42]	FERNANDES L, O’CONNOR M. Data governance and data stewardship. Critical issues in the move toward EHRs and HIE[J]. Journal of AHIMA, 2009, 80(5): 36-39.
[43]	BEHRINGER G, HIZLI M. Data Governance: State-of-the-Art[C/OL]// AHLEMANN F, SCHÜTTE R, STIEGLITZ S. Innovation Through Information Systems. Cham: Springer International Publishing, 2021: 687-699. DOI:10.1007/978-3-030-86797-3_45.
[44]	MAHANTI R. Introduction to Data, Data Governance, and Data Management[M/OL]//MAHANTI R. Data Governance and Data Management. Singapore: Springer Singapore, 2021: 1-3. https://link.springer.com/10.1007/978-981-16-3583-0_1.
[45]	ABRAHAM R, SCHNEIDER J, VOM BROCKE J. Data governance: A conceptual framework, structured review, and research agenda[J/OL]. International Journal of Information Management, 2019, 49: 424-438. DOI:10.1016/j.ijinfomgt.2019.07.008.
[46]	梅宏. 数据治理之论[M]. 北京: 中国人民大学出版社, 2020.
[47]	NIELSEN O B. A Comprehensive Review of Data Governance Literature[J/OL]// Selected Papers of the IRIS, 2017(Nr 8): 3. https://aisel.aisnet.org/iris2017/3/.
[48]	SOLOMONIDES A. Research Data Governance, Roles, and Infrastructure[M/OL]//RICHESSON R L, ANDREWS J E. Clinical Research Informatics. Cham: Springer International Publishing, 2019: 291-310. http://link.springer.com/10.1007/978-3-319-98779-8_14.
[49]	刘莉, 司莉. 科学数据治理实践:内容体系与发展趋势[J]. 情报理论与实践. 2023, 46(12): 175-182.
[50]	张娟, 张志强, 阮伟南, 等. 科技强国最新数据战略及其实施态势分析[J]. 世界科技研究与发展, 2021, 43(3):286-298.
[51]	EKE D O, BERNARD A, BJAALIE J G, et al. International data governance for neuroscience[J/OL]. Neuron, 2022, 110(4): 600-612. DOI:10.1016/j.neuron.2021.11.017.
[52]	DAVIS R. Data protection laws and regulations in China[J]. Journal of Cybersecurity Policy, 2020, 12(4): 345-367.
[53]	SHELTON S. The EU data act and its implications[J]. European Data Law Review, 2019, 22(1): 15-27.
[54]	刘先瑞, 司莉. 科学数据伦理治理:政策框架与路径——以英国为例[J/OL]. 现代情报:(录用定稿)[网络首发2024-08-01].
[55]	TRUBEK D M. Soft law and the legitimation of global governance[J]. Journal of International Law, 2015, 7(2): 123-147.
[56]	廖方宇, 胡良霖, 王健, 等. 科学数据安全标准研究与工作建议[J]. 科学通报, 2024, 69(9): 1142-1148.
[57]	刘碧琦. 美欧《隐私盾协议》评析[J]. 国际法研究, 2016(6):35-47.
[58]	刘文杰. 美欧数据跨境流动的规则博弈及走向[J]. 国际问题研究, 2022(6):65-78+136.
[59]	桂畅旎, 任政, 熊菲. 美欧跨境数据流动规则演变及启示[J]. 信息安全与通信保密, 2023(11): 15-24.
[60]	隆云滔, 王磊, 刘海波. 跨境数据流动治理规则研究[J]. 数据与计算发展前沿, 2023, 5(1): 74-84.
[61]	单文华, 邓娜. 从“数据隐私框架”看欧美数据跨境流动的规则博弈[J]. 太平洋学报, 2024, 32(1):44-56.
[62]	GREEN E D, WATSON J D, COLLINS F S. Human Genome Project: Twenty-five years of big biology[J/OL]. Nature, 2015, 526(7571): 29-31. DOI:10.1038/526029a.
[63]	AMANN R I, BAICHOO S, BLENCOWE B J, et al. Toward unrestricted use of public genomic data[J/OL]. Science, 2019, 363(6425): 350-352. DOI:10.1126/science.aaw1280.
[64]	CLARKE N, VALE G, REEVES E P, et al. GDPR: an impediment to research?[J]. Irish Journal of Medical Science, 2019, 188(4): 1129-1135. DOI:10.1007/s11845-019-01980-2. pmid: 30734900
[65]	PELOQUIN D, DIMAIO M, BIERER B, et al. Disruptive and avoidable: GDPR challenges to secondary research uses of data[J]. European Journal of Human Genetics, 2020, 28(6): 697-705. DOI:10.1038/s41431-020-0596-x. pmid: 32123329
[66]	CHASSANG G. The impact of the EU general data protection regulation on scientific research[J/OL]. ecancermedicalscience, 2017, 11:709. DOI:10.3332/ecancer.2017.709.
[67]	QUINN P. Research under the GDPR - a level playing field for public and private sector research?[J/OL]. Life Sciences, Society and Policy, 2021, 17(1): 4. DOI:10.1186/s40504-021-00111-z.
[68]	EISS R. Confusion over Europe’s data-protection law is stalling scientific progress[J]. Nature, 2020, 584(7822): 498-498. DOI: 10.1038/d41586-020-02454-7.
[69]	RABESANDRATANA T. European data law is impeding studies on diabetes and Alzheimer’s, researchers warn[J/OL]. Science, 2019-11-20. DOI:10.1126/science.aba2926.
[70]	Opinions \| European Data Protection Supervisor[EB/OL]. [2024-01-23]. https://edps.europa.eu/data-protection/our-work/our-work-by-type/opinions_en.
[71]	如何理解和应对美国限制访问敏感个人数据行政命令[EB/OL]. https://www.secrss.com/article/64086.
[72]	MESZAROS J, HO C. AI research and data protection: Can the same rules apply for commercial and academic research under the GDPR?[J/OL]. Computer Law & Security Review, 2021, 41: 105532. https://doi.org/10.1016/j.clsr.2021.105532.
[73]	MOHAMMAD A M, JESUS M, FANAEI S D, et al. Artificial intelligence ethics and challenges in healthcare applications: A comprehensive review in the context of the European GDPR Mandate[J/OL]. Machine Learning and Knowledge Extraction, 2023, 5(3): 1023-1035. https://doi.org:10.3390/make5030053.
[74]	Bits of Power: Issues in Global Access to Scientific Data[M/OL]. Washington D C: National Academies Press, 1997: 5504. http://www.nap.edu/catalog/5504. DOI:10.17226/5504.
[75]	魏鑫, 汪洋. 我国科学数据出境管理对策研究[J]. 农业大数据学报, 2024, 6(2): 156. DOI:10.19788/j.issn.2096-6369.000036.

基于规则的科学数据安全治理框架：理解数据“保护-利用”失衡及挑战的新工具

Rule-Based Framework for Scientific Data Security Governance: A New Tool for Understanding the Imbalance and Challenges of Data Protection and Utilization

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[2]	孙雨潇, 李艳丽, 李峰, 陈谦. 国内外科学数据共享现状研究与发展建议[J]. 农业大数据学报, 2022, 4(2): 88-98.
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