Analysis of the Fragmentation and Coordination Path of International Rules for the Protection of Personal Data Rights and Interests in the Era of Big Data
DOI:
https://doi.org/10.54097/c5vq0f95Keywords:
Era of big data, the rules for personal data rights, fragmented interests.Abstract
As the era of big data progresses in depth, while cross-border data flow has become a new engine for global economic growth, it also poses severe challenges to personal data rights. The data governance rules adopted by various countries to address this issue exhibit a distinct "fragmentation" feature, posing significant resistance to international cooperation and corporate compliance. This article focuses on this topic. By using the comparative research method, case study method and legal text analysis method, the core differences in regulatory systems and cross-border rules among the three major data governance models of the European Union, the United States and China were systematically analyzed. By analyzing typical cases such as the "Schrems II" case and the Didi incident, this paper proposes a multi-level coordination path centered on building "interoperability", aiming to provide theoretical references and practical suggestions for constructing a fairer, more efficient and safer global digital governance model.
Downloads
References
[1] Liu R., Zhou J. Y. Policy issues and countermeasures of cross-border data flow in China's digital economy. Keji Zhongguo Science & Technology China, 2021, (4): 53 – 56.
[2] Long J. T. Protection path of antitrust law for personal privacy rights in the big data era. Renmin Luntan People's Tribune, 2022, (24): 112 – 115.
[3] Jiang H., Chang P. Y. The Normative Construction of Cross-border Data Flow from the Perspective of the Basic Categories of Law. Journal of Yantai University (Philosophy and Social Sciences Edition). 2025.
[4] Liu R., Zhou J. Y. Policy issues and countermeasures of cross-border data flow in China's digital economy. Keji Zhongguo Science & Technology China, 2021, (4): 53 – 56.
[5] Long J. T. Protection path of antitrust law for personal privacy rights in the big data era. Renmin Luntan People's Tribune, 2022, (24): 112 – 115.
[6] Hua J. Privacy protection in the era of artificial intelligence: Analysis of provisions in EU General Data Protection Regulation and related proposals for new regulations. Lanzhou Academic Journal, 2023, (6): 97 – 108.
[7] Jiang H., Chang P. Y. The Normative Construction of Cross-border Data Flow from the Perspective of the Basic Categories of Law. Journal of Yantai University (Philosophy and Social Sciences Edition), 2025.
[8] Tang Z. Fragmentation of international rules on cross-border data flow and coordination paths. Jiangxi Social Sciences, 2025, 45 (6): 120 - 130.
[9] Cate F. H., Mayer-Schönberger V. Notice and consent in a world of Big Data. International Data Privacy Law, 2013, 3 (2): 67 – 73.
[10] Schwartz P. M., Peifer K. N. Transatlantic data privacy law. Georgetown Law Journal, 2017, 106 (1): 115 – 179.
[11] Kuner C. Transborder data flows and data privacy law. Oxford: Oxford University Press, 2021.
[12] European Commission. EU–U.S. Data Privacy Framework: Adequacy decision. Brussels: European Commission, 2023.
[13] Makulilo A. B. The long arm of GDPR in Africa: Reflection on data privacy law reform and practice in Mauritius. In The Right to Privacy Revisited (pp. 121 - 150). Routledge, 2021. DOI: https://doi.org/10.4324/9781003252191-6
[14] Xiong G., Zhang S. The extraterritorial application of China’s personal information protection norms: An examination from an international comparative perspective. Ji Bijí, 2025. Advance online publication.
[15] Organisation for Economic Co-operation and Development (OECD). OECD guidelines on the protection of privacy and transborder flows of personal data. Paris: OECD Publishing, 2013.
[16] European Commission. Standard contractual clauses for the transfer of personal data to third countries pursuant to Regulation (EU) 2016/679. Official Journal of the European Union, 2021.
[17] European Data Protection Board (EDPB). Recommendations 01/2020 on measures that supplement transfer tools to ensure compliance with the EU level of protection of personal data. 2021.
[18] Cate F. H., Mayer-Schönberger V. Notice and consent in a world of Big Data. International Data Privacy Law, 2013, 3 (2): 67 – 73. DOI: https://doi.org/10.1093/idpl/ipt005
[19] Shokri R., Shmatikov V. Privacy-preserving deep learning. Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, 2015: 1310 – 1321. DOI: https://doi.org/10.1145/2810103.2813687
[20] Cheng L., Liu F., Yao D. Enterprise data breach: Causes, challenges, prevention, and future directions. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2017, 7 (5): e1211. DOI: https://doi.org/10.1002/widm.1211
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Highlights in Business, Economics and Management
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
