Filed under data-economy
Every brief tagged "data-economy".
- § 13 · DATA-PROPERTY-RIGHTS
Two Paths for the 'Right to Hold Data' — and Why the Narrow One May Add Little
Hong Yanqing (洪延青, 网安寻路人) works through the most unstable concept in China's 'separation of three rights' data-property framework — the Right to Hold Data (数据持有权). He pushes two readings to their logical ends. Path 1, the official 'complete separation' (三权完全切割): if the rights to hold, use, and operate data are truly independent, the holding right shrinks to a bare 'lawful-control state' whose only content is defensive — and that defense is already provided, against the world, by PIPL Article 10, DSL Article 32, the Network Data Security Regulation, and Article 13 of the Anti-Unfair Competition Law, so its incremental value as a standalone property right is thin. Path 2, the 'mother-right' reconstruction (持有权母权化): redefine 'holding' from factual control to a normative control that contains utilization potential, so the rights to use and operate are carved out from within it. DCC's read for overseas counsel: in Chinese data deals the tradeable substance sits in the rights to use and operate plus contract, registration, and compliance — not in 'who holds the data' — and China's data-property theory is still genuinely unsettled.
- § 14 · DATA-PLEDGE-FINANCING
Data Pledge Financing in China: What Is Actually Being Pledged, and Where the Law Gets Stuck
As Chinese banks and data exchanges experiment with data pledge financing (数据质押融资), a threshold question remains unresolved: what, legally, is being pledged? Chen Yiqian of Shenzhen Data Exchange walks through the two available routes under the Civil Code — chattel pledge (动产质权) and rights pledge (权利质权) — and the three operational problems that make chattel pledge difficult and the two doctrinal barriers that make rights pledge harder still. The analysis converges on a practical conclusion: chattel pledge via a third-party data custodian is the most workable path today, while data property rights and data intellectual-property rights both remain insufficiently legalised to support a reliable pledge. For overseas counsel advising on China data-asset financing, the gap between policy ambition and legal infrastructure is the central risk to price. Connects to the broader data property-rights registration project and the unresolved question of how data enters corporate balance sheets.
- § 15 · ANONYMIZATION
Reviving a Zombie Provision — Xu Ke's Concentric-Circle Reconstruction of the Anonymization Regime
Xu Ke (UIBE) calls PIPL Article 4's anonymization carve-out a 'zombie provision' (僵尸法条) — on the books, never used, and one of the biggest blockages in the data-element market. His diagnosis: the zombie state is caused not by the text but by three unaddressed worries (processors fear the standard is unattainable or value-destroying; regulators fear anonymization becomes an evasion tool; users fear it's a hollow promise). His cure is a concentric-circle architecture that maps three risk types (systemic / operational / residual) onto three layers of anonymity (presumptive / determined / trust). This is the most complete academic blueprint yet for making the anonymization clause operational — and it pairs directly with TRIMPS's risk-based, recipient-relative reading.
- § 16 · DATA-PROPERTY-RIGHTS
The 'Rights Block' — Xu Ke's Structural Theory Behind China's Data-Property Framework
Xu Ke's highly-cited (255×) 政法论坛 article on the structure of data rights — the theoretical scaffolding that the Data 20 Articles' three-rights framework rests on. He maps the field's two warring paradigms (formalist 'empowerment' vs substantivist 'conduct regulation'), argues both fail alone, and integrates them via a 'reflexive law' approach. The payoff is a taxonomy of three possible rights structures — rights-ball, rights-bundle, rights-block — and the case that the 'data rights block' (数据权利块) best fits data's 'one principle, many manifestations' character. For overseas counsel, this is the conceptual map that explains why Chinese data rights are structured the way they are — and why Western property and IP analogies keep failing.
- § 17 · DATA-ASSET
When Does Data Become an Asset? Xu Ke on Identifying and Defining Data Assets
Xu Ke (UIBE), writing for a practitioner audience, draws the line between data resource (国家视角, public/strategic) and data asset (市场主体视角, commercial), then between the broad sense (anything that creates value for the enterprise) and the narrow sense (meets the MOF accounting-standard test for on-balance-sheet recognition — owned/controlled, generates economic benefit, reliably measurable). He works the three-rights framework into operational boundaries by data type (personal / enterprise / government) and flags the practical questions overseas counsel face when a Chinese counterparty wants to put data on its balance sheet.
- § 18 · DATA-ECONOMY
Tang Linyao — Data-Broker Derivative Harms and the 'Data Integration Analysis Framework'
Tang Linyao (Chinese Academy of Social Sciences) maps the regulatory gap for data-broker derivative harms — the harms that arise not from direct PI leakage but from the integration and aggregation activity that data brokers themselves perform. The analytical core: a vertical / horizontal data-relations framework that explains why existing PIPL-style protection (vertical-relationship-focused) systematically fails to address horizontal-relationship harms; and the 'abstract risk substantialization' doctrine borrowed from US precedent and EU GDPR to bring data-broker risk into ex-ante regulatory scope. Operationally, Tang proposes a 'Data Integration Analysis Framework' with concrete tiering (三高 / 双高 / 单高 / 三低) that translates academic doctrine into compliance-program-grade controls. Applied to a real Shenzhen Data Exchange listing as worked example.