The basic concepts related to assets, data, and data assets have been introduced last time. Next, on this basis, the data attributes in data assets are explored, in order to understand the concept of data assets more systematically and comprehensively. Data attributes in data assets include storability, readability, simultaneous sharing and non-depletion.
1. Storability
Data storage is a necessary condition for the use, measurement and accounting of data assets. The network space storage mode reduces management costs, and users can use data unlimited times, high frequency, and high efficiency, thereby creating huge economic benefits. As a store of value, things that are not storable cannot be defined as assets.
2. Readability
These data widely exist in electronic data in virtual spaces such as computer networks, communication networks, the Internet of Things, and the cloud. Computers, mobile phones, CDs, disks, and hard drives are important carriers of data. When used, the information contained in these data can be read and recognized by certain reading devices.
3. Simultaneous sharing
Compared with other traditional assets, data assets have the characteristics of simultaneous sharing. For example, many network users can browse and download data that meets their needs at the same time; while other traditional assets cannot be shared by multiple users at the same time due to form restrictions. Data assets can be shared by multiple users at the same time, enabling them to be used at high speed and high frequency, becoming an important support for the explosive growth of the digital economy.
4. The data of data assets is non-depletable
The data itself will not change over time, but the value of the data can be reduced or increased, which is the difference between data assets and other traditional assets. The value timeliness of some data is stronger than that of fixed assets in the traditional sense, and its value density may decrease over time. However, in the process of continuous expansion of data scale and innovation and development of data technology, large-scale data fusion in different fields has derived new business forms and new growth points, explored more fields, and created more value. Therefore, at this time, the data assets will not decrease, but will increase in value significantly.
However, at present, there is no consensus on which type of assets data assets are included in the accounting. Some argue for the inclusion of non-produced assets, while others argue that productive assets should be included.
The productive attributes of data assets are relatively clear. According to the labor value theory of Marxism, the generation of data assets includes the consumption of labor in the process of data collection, processing, analysis and storage, and is the result of labor processing.
The platform covers 360-degree information of the enterprise, such as basic information (shareholder information, registration changes, branches, historical equity trajectory, historical executives, etc.), negative information (administrative punishment, judgment documents, persons subject to enforcement, dishonest persons subject to enforcement, court hearings, etc.) Announcements, court announcements, case filing information, final case, exposure platform, etc.), business information (bidding clues, bidding winning clues, recruitment information, construction project information, public opinion information, fire inspections, random inspection information, double random inspection information), Asset information (patents, trademarks, software copyrights, work copyrights, management system certification, compulsory product certification, etc.) full-dimensional data of many enterprises.
According to the classification standard of national economic accounting standards, production assets are non-financial assets composed of the output of institutional units in the production process. Data assets conform to this guideline. Data assets are formed during the production process, which may be a specially produced output or a non-specially produced output. For example, the data assets of hospitals, banks and other departments are the output of their non-specialized production. The data of these departments are generally derived from the informatization of transactions in actual production. In addition, the main production process of professional data platforms (Global Meteorological Data Network, National Bureau of Statistics website, China Price Information Network, etc.) is data collection, retrieval, capture, storage, transmission and display, and data assets are the output of their special production . Some of these data are provided free of charge to users who need them in a shared manner, and some are sold in the market at a high price, which should be included in the accounting scope of data products and data assets as the main product.