[Editor to fill: 200-word overview of how the Data Economy domain differs from data security and personal-information protection — the focus here is circulation and ownership rather than protection and consent.]
§ DOMAIN · DATA ECONOMY
Data Economy.
数据要素与数据产权
China's emerging regulatory framework for treating data as an economic factor of production — public-data resources, data-property rights, data-asset registration, and the rules governing how data can be authorized for operation, traded, and circulated. Distinct from data security and personal-information protection, this domain tracks the rules that turn data into a tradeable asset.
The legal corpus.
6 laws.
- Data Twenty Opinions Opinions of the CPC Central Committee and the State Council on Building a Basic Data System to Better Play the Role of Data Elements 中共中央 国务院关于构建数据基础制度更好发挥数据要素作用的意见
- DRAFT Data Property Rights Registration Work Guide (Trial) — Draft for Public Consultation 数据产权登记工作指引（试行）（公开征求意见稿）
- Data Terms Batch 1 Explanation of Common Terms in the Field of Data (First Batch) 数据领域常用名词解释（第一批）
- Data Terms Batch 2 Explanation of Common Terms in the Field of Data (Second Batch) 数据领域常用名词解释（第二批）
- RULE Interim Measures for the Registration and Administration of Public Data Resources 公共数据资源登记管理暂行办法
- RULE Implementation Specifications for Authorized Operation of Public Data Resources (Trial) 公共数据资源授权运营实施规范（试行）
In this domain.
18 briefs.
- § 01 · JUDICIAL
Datatang v. Yinmu — China's First Ruling on a Data-IP Registration Certificate, and Why Open-Sourced Data Is Still Protected
A consolidated case study of 数据堂诉隐木科技 (Datatang v. Yinmu) — the Beijing IP Court's June 2024 appeal ruling, widely called China's first case on the evidentiary effect of a data-IP registration certificate. The dispute: Datatang built voice datasets for AI training, open-sourced some under a license; Yinmu took and redistributed them in the same data-services market. DCC synthesizes four commentaries (the case report, a Tsinghua analysis, and two Shenzhen Data Exchange DEXC+ deep-dives) into the four holdings that matter for overseas counsel: (1) a data-IP registration certificate is prima facie evidence of property-type interests and lawful sourcing — but not an absolute property right (property-rights-statutism); (2) open-sourced data, though neither trade secret nor copyrightable compilation, is protectable under the Anti-Unfair Competition Law's general clause; (3) the protection hierarchy (compilation work → trade secret → AUCL Art. 2); and (4) whether the taker honored the open-source license is the hinge for 'improper conduct.'
- § 02 · 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.
- § 03 · 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.
- § 04 · 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.
- § 05 · 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.
- § 06 · 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.
- § 07 · 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.
- § 08 · DATA-PROPERTY-RIGHTS
Who Is the 'Data Processor' Under the Three-Rights Framework — NDA's Farm-Equipment Hypothetical
NDA's official 政策解读 on the threshold question that every three-rights allocation depends on: who is the 'data processor' and who is the 'information subject'? NDA uses a farm-equipment hypothetical — a farm rents tractor, irrigation, and fertilizer equipment from three different vendors; cultivation data is captured in the process — to work through who collects, who decides processing purposes, and how the property-rights regime balances the data-processor's commercial interest against the information-subject's rights to access copies of relevant data. The piece sketches the basic information-subject vs. data-processor dichotomy that anchors the entire downstream data-element regime, and surfaces the access-to-data right (data portability for commercial entities) that overseas counsel often miss.
- § 09 · DATA-PROPERTY-RIGHTS
Cloud, BPO, and Other Entrusted-Processing Arrangements: Why the Processor Doesn't Get the Rights
NDA's official 政策解读 on a tactically critical sub-question of the three-rights framework: when a data processor outsources storage, processing, or analysis to a third-party service provider — typical cloud, BPO, or e-government-system arrangements — does the entrusted party acquire any of the three property rights? NDA's clear answer: no. The entrusted processor (受托人) is not a 'data processor' in the property-rights sense — it merely executes instructions on behalf of the data processor (the principal). It cannot use the data outside the entrusted scope, cannot transfer the data into market circulation, and cannot apply the data to its own debt repayment or bankruptcy distribution. The line is anchored to the Civil Code's contract-of-mandate rules — a long-standing piece of Chinese commercial law extended cleanly into the data-element regime.
- § 10 · TOKENS
Cold Water on 'Token Trading' — Wang Qinglan on the NDA's High-Quality Data Set Initiative
In March 2026, the National Data Administration released the *Implementation Plan for Promoting High-Quality Industry Data Set Construction (Draft for Public Consultation)*, which explores a 'token (词元) based value system' and 'token trading as a new transaction mode' for high-quality data sets. The Chinese AI policy community immediately heralded the move as 'revolutionizing data trading.' Wang Qinglan pours cold water: token is a measuring unit, not a magic transformer. AI tokens are not crypto tokens. The bottleneck in China's data-element market isn't measurement — it's supply, rights clarity, compliance cost, and data silos.
- § 11 · DATA-PROPERTY-RIGHTS
Will Judicial Review 'Reset' the Data Registration Rush? — Reading Wang Qinglan on the SPC's New Data Disputes Case Category
Wang Qinglan, head of compliance at a Chinese data exchange, asks what the Supreme People's Court's new 'data disputes' case category — effective January 1, 2026 — does to the data property rights registration certificates that institutions across the country have been issuing. Her argument: certificates issued through formal-only review will not survive substantive judicial scrutiny, and a single rejected certificate could erode trust in the entire registration regime. The path forward is a three-tiered protection model and aligned standards across regulators, registration institutions, and courts.
- § 12 · CROSS-BORDER
Mutual Trust Mechanisms for Cross-Border Data Flow — China's 'Trusted Data Space' Bet
Compliance Talker's global legal policy team analyzes three competing models for cross-border data mutual trust: the EU's 'rule trust' (adequacy + SCC), the US's 'market trust' (CLOUD Act + DPF), and China's 'technology trust' bet on Trusted Data Spaces (TDS). The NDA's November 2024 *TDS Development Action Plan 2024-2028* makes confidential computing, federated learning, and blockchain the technical layer through which China seeks to demonstrate cross-border data flow can be 'usable but invisible.' For overseas teams, this is the most concrete view of where Chinese cross-border data infrastructure is heading.
- § 13 · DATA-FUNDAMENTALS
What Is Data, Really? — A Plain-Language Primer on Rules and Compliance
What does it actually mean to call something 'data,' and what turns raw recordings into a data asset? Wang Qinglan uses a toy storage room metaphor to walk through the foundational concept overseas readers often skip: data is not just 'records' — it's records made under rules. Master data, metadata, ontology, the three-tier compliance taxonomy (legal / ethical / promised), and the three-step compliance workflow (select / allocate / execute) — all anchored in a concrete example a non-specialist can follow.
- § 14 · DATA-GOVERNANCE
Data Governance vs. Data Management vs. Data Compliance — A Plain-Language Disambiguation
Wang Qinglan disambiguates three terms that compliance and data teams habitually conflate: data governance, data management, and data compliance. Using a 'data manor' metaphor (the family council vs. the steward team vs. the community monitor), she maps each function to its job — setting direction, executing efficiently, and operating sustainably within external rules and self-imposed commitments. The piece is useful precisely where bilingual confusion is highest: 'data governance' in English carries different connotations than 数据治理 in Chinese practice.
- § 15 · DATA-PROPERTY-RIGHTS
What Does Data Registration Actually Confirm? — A Doctrinal Reading
Long before the SPC's January 2026 'data disputes' case category started squeezing data registration certificates against judicial review, Wang Qinglan had already written the foundational critique: data registration does not 'confirm rights' because there are no legal data rights to confirm. The Data 20 Articles created data property rights, not data legal rights, and Chinese property rights are not Article-conferred civil rights. Registration certificates are 'trust credentials,' not 'rights certificates.' This is the doctrinal essay overseas counsel should read before the SPC sequel.
- § 16 · DATA-EXCHANGES
On-Exchange vs. Off-Exchange Data Trading — A Uniquely Chinese Market Structure
Why does China have data exchanges? Wang Qinglan's piece opens with an observation overseas readers will recognize: 'When you tell foreigners about China's on-exchange data trading market, you get blank stares — because exchange-organized data trading is uniquely Chinese.' The analogy she offers — Shenzhen Data Exchange is to data what the Shenzhen Stock Exchange is to securities — unlocks the architecture. Five tiers of trading venues by public-risk level. Three waves of Chinese data-exchange evolution. And the operational meaning of why on-exchange and off-exchange trading coexist.
- § 17 · DATA-ECONOMY
What Is Actually Traded on China's Data Exchanges — A Bakery Metaphor
Per the Shenzhen Provisional Measures for Data Trading Administration, four categories of object can be traded on a Chinese data exchange: data products, data services, data tools, and other regulator-approved objects. Wang Qinglan walks through what each means in plain language with a bakery metaphor — wheat (raw data) becomes flour (data resources) becomes cakes (data products); a baker is a data service; the oven is a data tool. The piece is useful precisely because it answers a question overseas teams rarely think to ask: what are the data exchanges actually selling?
- § 18 · PUBLIC-DATA
Case Study — A Public-Data Operator Hands Personal Data to a Bank. Two Compliance Failures.
A real-case analysis from Wang Qinglan. A state-affiliated auction company holds the public-data operating right for vehicle license-plate auction data. A bank persuades it to hand over the personal data of winning bidders. The bank builds a targeted credit product and pays the auction company RMB 12 million a year in revenue share. Two compliance failures: (1) no individual consent under PIPL; (2) no credit reference business license under the Credit Reference Industry Regulation and Credit Reference Business Measures. Public-data authorized operation does not displace the credit reference licensing regime.