数据要素市场培育：法律难题、域外经验与中国方案

数字经济时代，数据继土地、劳动力、资本、技术之后成为第五大生产要素。目前我国数据权属确定的法律制度不够完善，数据要素市场交易的法律制度尚未建立，数据要素市场监管的法律制度不够健全，这都制约了我国数据要素市场发展。为了培育数据要素市场，应以数据生产者与数据处理者为划分标准，建立“数据生产者（扩展权利)—数据处理者（有限产权)”的数据产权制度；以“降低制度成本—减少交易成本”的思路完善数据要素市场交易相关规则；以“事前预防与事后规制相结合”的方式完善数据要素市场监管法律制度。

Cultivating Data Factor Market: Legal Dilemmas,Foreign Experiences and Chinese Countermeasures

With the development of algorithms and computing power, the mass available data continues to play a role in improving productivity. This paper gives answers to question of how data become the new factor of production and analyze the theoretical and practical basis of data as a new factor of production, and then explores the legal issues related to data ownership, data trading rules and data market supervision. These three aspects are closely related to the cultivation of data market. The purpose of this paper is to analyze these legal problems and their solutions in Europe and the United States, and finally put forward the strategies and methods to deal with the failure of data market and cultivate China′s data market. To be specific, data market cultivation is faced with three problems. The first is the problem of property right system of data. The uncertainty of the ownership of personal and non-personal data hinders the development and utilization of data, making the data trading inefficient. The second is the problem of data market trading rules, which is manifested as the single function of data trading platform and the homogeneity of data products, making trading outside the platform a prevalence. In addition, there are various classification standards of data products, and unified data product pricing standards are missing, which makes it impossible to form a unified data market. The third is the problem of data market regulation. Data unfair competition and data monopoly damage the legitimate rights and interests of data consumers and data enterprises, and disturb the order of the data market.#br#To solve these problems, this paper adopts the comparative research method. Through the analysis of the European Union and the United States' solutions and methods,it tries to find the experience that can be used for reference for the cultivation of China′s data market. As for the problem of property right system of data, there are debates on if data belongs to property, and some ideas such as individuals can own property right, quasi-property right or the right control over data can be strengthened. As for the problem of data market trading rules, whether personal data can be traded as property right involves the contradiction between personal privacy protection and data collection and use. It should be from the perspective of balancing privacy security and economic efficiency to answer and analyze whether personal data can be traded as property right. Making data a property right does not mean an absolute freedom of contract in data transaction. Personal data transaction should still be restricted by general contract rules and court discretion, and how to strengthen personal data control in enterprise data transfer and sharing should be explored based on sound technical infrastructure and regulatory framework. As for the problem of data market regulation, the United States adopts the methods of data antitrust and consumer data privacy protection. On the basis of strengthening personal data rights, the EU gives the digital gatekeeper prior obligations related to antitrust, consumer protection and privacy protection and other basic rights.#br#It is concluded that in order to cultivate China′s data market, it is necessary to innovate the regulatory rules of China′s data market based on absorbing foreign experience.As for the regulatory rules, the first is to establish a data property right system of integrating "data producer (extended rights) and data processor (limited property rights)", i.e., to establish the basic principle of "who produces, who owns" in data property rights. On this basis, the corresponding property rights are allocated to the data processor, taking into account the non property rights and property rights of the original data producer. The second is to improve the trading rules of data factor market with the idea of "reducing institutional cost—reducing transaction cost", which means to guide the comprehensive pilot by industrial policy so as to optimize the structure of data trading platforms, reduce transaction cost by scientific and reasonable standard of data product classification, clarify data pricing rules and pricing elements, and strengthen the price management and supervision of data elements. The third is to improve the legal system of data factor market′s supervision by combining pre-prevention and post-regulation. In order to prevent possible data anti-competitive and monopolistic behaviors, the main content of pre-prevention is classified management, subdivision of actors′ responsibilities and prior declaration. Post-regulation mainly includes the penalties for abuse of market dominance, unfair competition and other administrative or criminal penalties, and it should be specified only after the revision and improvement of relevant laws, so as to jointly promote the healthy and orderly development of data market by combining with the pre-prevention.#br#