Filed under data-economy
Every brief tagged "data-economy".
- § 01 · 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.
- § 02 · 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.
- § 03 · 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.
- § 04 · 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.
- § 05 · DATA-PROPERTY-RIGHTS
Wang Nian — Data Source's Rights as a 'Fair Use' Right Alongside the Three Rights
Wang Nian (Tsinghua Law) takes on the unresolved fourth-right question in the Data 20 Articles framework: what is the data source's right (数据来源者权), and how does it relate to the three rights (hold/use/operate)? Drawing on the 'data symbiosis' (数据共生) framework from the ALI-ELI Data Economy Principles and the EU Data Act, Wang argues that pre-existing legal entitlements — privacy, PI rights, IP, trade secrets — cover only part of the source's interest, leaving a residual that needs an independent legal protection. He frames the data-source right as a 'fair use right' (公平使用权): a contractual-relationship right against the specific data processor, distinct from the property-style three rights, that captures the value contribution of the source's participation in data co-creation. The corporate-data-portability analog DCC flagged in our NDA brief gets its doctrinal foundation here.
- § 06 · DATA-PROPERTY-RIGHTS
NDA Explains the Three-Rights Framework — A Plain-Language Walk-Through from the Regulator Itself
The National Data Administration's official 政策解读 (policy interpretation) on the three-rights framework — the right to hold, the right to use, and the right to operate data — established by the Data 20 Articles. NDA walks through what each right means, illustrative scenarios (group-company data subsidiaries; hospital-pharma research pools; data-broker commission arrangements), how the rights relate to each other (independently severable; non-exclusive across parties for the same data), and why the structural-separation design was chosen over a unitary-ownership model. The clearest available statement of the regulator's own intent on the framework that anchors every downstream rule — data-resource registration, data-property-rights registration, FTZ data-circulation negative lists, on-floor / over-the-counter trading rules.