Recently, the Central Committee of the Communist Party of China and the State Council issued the Opinions on Building a Data Base System to Give Better Play to the Role of Data Elements (hereinafter referred to as the "Twenty Data Articles"), marking the introduction of a high-level top-level design of the data base system. The "Twenty Rules of Data" clearly proposes to establish a data element circulation and trading system that is compliant and efficient and combines both inside and outside the market. "China's data scale and magnitude have already met the conditions for building a world leading super large data market." Zheng Dingxiang, president of the Shenzhen Information Service Industry Blockchain Association, told the Securities Daily that the establishment of a compliant and efficient data element circulation and trading system that combines both on and off the market will help China achieve the superposition of advantages of online super large data and offline super large markets, Give play to the role of data as a core strategic resource, turn "demographic dividend", "land dividend", "technology dividend", "capital dividend" into "data dividend", and seize the priority of global competition for new tracks in the digital economy. Public data is proposed according to the government's guidance on pricing and paid use of "Twenty Rules of Data", and the whole process of data compliance and regulatory rules system is improved. Support the exploration of diversified pricing models and price formation mechanisms that conform to the characteristics of data elements, promote the paid use of public data for digital development under the guidance of the government, and the independent pricing of enterprises and personal information data market. We will strengthen the construction and supervision of the corporate data compliance system, crack down on black market transactions, and ban illegal data circulation industries. Chen Xiaohua, an expert in the review of major new infrastructure projects of the Ministry of Industry and Information Technology and the executive director of the Metacosmic Industry Collaborative Innovation Center in the Science Park of Beijing University of Posts and Telecommunications, told the reporter of the Securities Daily that if the pricing model and price formation mechanism of data elements can be determined, it will greatly improve the distortion of current data element market pricing and unfair distribution of interests, and enrich the existing data whole process compliance and regulatory rule system, It is of great strategic significance to promote data trading and improve the market-based allocation mechanism of data elements. "The externalities, heterogeneity, value spillovers, multiple transaction scenarios and other characteristics of data make it difficult to directly apply the market approach, income approach, cost approach, etc. commonly used in asset value evaluation to data asset pricing, and it is necessary to innovate the traditional price theory when pricing." Zheng Dingxiang believes that the value of data needs to be reflected in circulation and use, and can consider relying on blockchain technology and adopting a unique way of ex post pricing, Meet the demand of data pricing. Blockchain technology can provide a whole process tracking service for the confirmation and use of data. Data can be used for fee settlement. The smart contract function of the blockchain can automatically execute the agreement price. Data circulation will be more intelligent and automatic, data circulation will be more efficient, and the cost of data use will be reduced. Zhao Yongxin, deputy director of the Yuan Universe Industry Committee of China Mobile Communications Federation and professor of Hebei University of Finance, told the reporter of Securities Daily that different data pricing rules and pricing models are different. It is suggested to start with cost pricing for government and other public data, and build a model combining data cost, data quality and data privacy content; For the enterprise and personal information data, the pricing model and algorithm can be customized according to the combination degree of the data and specific application scenarios