Recently, all parties concerned have actively promoted the construction of the data element market, and the exploration of data assetization has been significantly accelerated. For example, some organizations have released an integrated platform for accounting and processing of enterprise data resources to help enterprises strengthen data resource management and facilitate "entry into the table"; Some companies have implemented the chief data officer mechanism, aiming to break the fragmented model of data resource development and utilization.
A data asset is a data resource that is legally owned or controlled, can be measured, and brings economic and social value to the organization. The so-called data capitalization refers to the transformation of data resources into tradable commodities, so that the potential value of data resources can be fully released, with the purpose of bringing more economic benefits to the organization through data.
Data is an important factor of production and a basic strategic resource of the country, and it is inseparable from data assetization to play the role of data elements. The previously issued documents such as the "Opinions on Building a Data Basic System to Better Play the Role of Data Elements", the "14th Five-Year Plan" for the Development of the Digital Economy, and the Interim Provisions on the Accounting Treatment of Enterprise Data Resources have both top-level designs and specific measures, forming a strong synergy to promote data assetization. Many regions have also issued relevant laws and regulations to promote data assetization, and some places have carried out pilot trials to accelerate the pace of data assetization exploration. It should be noted that the new characteristics of data elements are more complex, which will pose new challenges to traditional property rights and circulation norms. Supporting mechanisms such as data element confirmation, pricing, trading, and supervision have not yet been formed, and problems such as difficulty in confirming and pricing data transactions have restricted the process of data assetization to a certain extent. In this regard, more measures should be taken to solve the problem.
Clear and standardized ownership is the basis for realizing data assetization. It is necessary to actively explore filling the legal gaps in data rights confirmation, further improve relevant policies, and accelerate the establishment of separate property rights operation mechanisms such as the right to hold data resources, the right to process and use data, and the right to operate data products, so as to provide basic institutional safeguards for activating the value of data elements. In the hierarchical management of data, scientific classification may be carried out based on the sensitivity of the data, reasonably dividing the rights, responsibilities, and interests of the data, giving full play to the allocation attributes of data property rights, and encouraging the rational and lawful use of data resources. In terms of technical support of data, encryption technologies such as blockchain and digital watermarking can be used to ensure the uniqueness and full traceability of property rights in the process of data circulation, storage, and utilization, and to prevent data elements from being stolen, tampered with, and copied.
Pricing valuation is an important guarantee for the valorization of data assets. It is necessary to accelerate the development of data asset valuation models, and explore the establishment of a unified and reasonable pricing system to ensure the fairness of data asset valuation. In terms of specific design, a data asset value evaluation index system can be established based on indicators such as cost, application value, brand value, and data quality. Among them, the cost dimension mainly includes the acquisition cost, development cost, and operation and maintenance cost of data assets. The application value dimension mainly includes the matching degree, reusability degree and scenario economy between data assets and application goals. The brand value dimension mainly includes the service level, credit level and data governance ability of the data seller. The data quality dimension mainly includes the scarcity, timeliness, and standardization of data assets.
In addition, it is necessary to accelerate the cultivation of standardized data trading platforms, promote the circulation of data elements, and realize the value of data elements. Focusing on the whole cycle of data openness, transaction sharing, data supervision and other elements, establish unified data transaction rules, form a multi-level intensive and efficient data trading market, and break the "information island" in the circulation of data elements. Continuously improve the mechanism and specification of the whole process of data transactions, explore the establishment of a transaction model with the characteristics of data elements, use market-oriented means to activate data and release value, and provide a platform foundation for the primary and secondary market transactions of data elements. Establish and improve regional cooperation mechanisms for data trading markets, promote market interconnection and regional cooperation, and accelerate the establishment of a unified national market system for the circulation and trading of data elements.
*:Economy**.