At the 2023 China International Digital Economy Expo, staff introduced the 5G+smart factory project to visitors. Xinhua News Agency reporter Luo Xuefeng's "Opinions of the Central Committee of the Communist Party of China and the State Council on Building a Data Infrastructure System to Better Play the Role of Data Elements" ("Twenty Data Articles") was released to the public in December last year, systematically laying out the "four beams and eight pillars" of the data infrastructure system, which is a programmatic document to promote the circulation, trading, and income distribution of data elements. The Ministry of Finance issued the "Interim Provisions on Accounting Treatment of Enterprise Data Resources" in August this year (hereinafter referred to as the "Interim Provisions"), which will be implemented from January 1, 2024, providing basic guidance for the inclusion of enterprise data resources in the table. The China Asset Evaluation Association issued the "Guiding Opinions on Data Asset Evaluation" (hereinafter referred to as the "Guiding Opinions") in September this year, laying the foundation for the smooth progress of data asset entry, trading, circulation, transfer, and other links. The Provisional Regulations and Guiding Opinions are both micro measurements of data assets, which can fully unleash the empowering effect of data on the real economy and assist in the implementation of digital economy policies. In the digital era, data has become one of the key drivers of economic growth and the core production factor driving the development of the digital economy. Data capitalization is an important way to release the value of data elements. But to fully tap into the potential of data, it is necessary to first address the issue of accurately estimating the value of data, which is particularly important for China, which is currently in the rapid development stage of the digital economy and technological innovation. Therefore, accelerating the construction of a data asset valuation system with Chinese characteristics has become an urgent task, which is of great significance in promoting data asset pricing, trading, and circulation, enriching and expanding data asset application scenarios, activating and improving the data element market, and improving the quality of data infrastructure construction. The data asset valuation system urgently needs to be constructed. As one of the most critical production factors in the digital economy era, data has become a fundamental strategic resource for the country. However, the current construction of the data element market is not yet complete, and the data asset valuation framework and system have not been established. This not only makes it difficult to fully realize the value of data assets, but also restricts the circulation and trading of data elements, hinders the market-oriented allocation process of data elements, and is not conducive to the construction of data infrastructure systems and the high-quality development of the digital economy. The definition of data asset ownership is unclear. Compared with traditional production factors such as land and capital, data, a new type of production factor, involves more complex entities and their ownership relationships. In the data element market, the three rights separation of data processing, holding, and operation is mainly achieved by separating and setting them separately. Due to the inherent characteristics of data production factors, the traditional three rights separation structure cannot be directly applied. In the data element market, the separation of three rights does not directly lead to the separation of the original rights subject. Therefore, it is necessary to clarify that the separation of three rights is the separation of rights rather than the separation of rights subjects. This is also an important prerequisite for promoting the development of the data element market. This complex issue of data asset ownership increases the difficulty of data asset valuation and affects the construction of valuation systems. Traditional asset valuation methods are limited. Data assets have characteristics that are different from traditional assets, namely non entity, dependent, non competitive