Research on the law of data element formation and value release
Wang Zeyu, Lu Ailin, Yan Shu
China Academy of Information and Communications Technology, Beijing 100191
Abstract : Based on the concept and historical analysis of data and production elements, it is proposed that data elements are gathered, sorted, and processed according to specific production needs. Computer data and its derivative forms participating in social production and management activities should be focused on as economic growth. New kinetic energy and the value of promoting production development. The value release approach of data elements is summarized, that is, the three values of business integration, digital decision-making, and circulation empowerment, which should be given full attention in the process of promoting the development of data elements.
Key words : data elements; data; production factors; tertiary value
Paper citation format:
Wang Zeyu, Lv Ailin, Yan Shu. Research on the Law of Data Element Formation and Value Release. Big Data [J], 2023, 9(2): 33-45.
WANG Z Y, LYU A L, YAN S. Research on the regularity of data factor formation and value release. Big data research[J], 2023, 9(2): 33-45.
0 Preface
On December 19, 2022, the "Opinions of the Central Committee of the Communist Party of China and the State Council on Building a Data Basic System to Better Play the Role of Data Elements" (hereinafter referred to as "Data Twenty") was released, which has attracted widespread attention from all walks of life in government, industry, academia and research. The "Twenty Articles on Data" is a programmatic document for my country to further promote the development of data elements. It clarifies the premise, main line, key points, goals and working principles of building a basic data system and giving full play to the role of data elements. Circulation and trading system, data element revenue distribution system, and data element governance system are the basic data system with Chinese characteristics. As a national policy document in the field of data elements, the "Twenty Articles on Data" has made special deployments for the four core links in the development of data elements, using basic systems to solve basic problems, in order to promote the orderly circulation and reasonableness of data in a wider range. Agglomeration and further promotion of data value transformation point out the direction.
At present, academia and industry have carried out in-depth discussions on data elements from multiple perspectives, such as data elementization conditions, unique attributes of data elements, data elements and economic growth, data basic system, data element market cultivation, data authorization and authorization. There have been a lot of research results in the protection of rights and interests, data valuation and pricing, and data circulation technology. Gao Fuping believes that data intelligence is the value production mode of data elements, and proposes that "originality", "machine readability" and "meeting certain quality requirements" are the three major conditions for data elementization. He Suyan believes that the factorization of data production is the process of transforming data from possible factors of production into actual factors of production. The above research reveals the basic conditions of data factorization, and the unique attributes of data give new endowments to its factorization. Guo Jing and others summed up 9 attributes of data from three dimensions of technology, economy and market. Yan Yu and others took virtuality, non-competitiveness, exclusivity and non-competition as the salient features of data elements. Li Yongjian further analyzed the data The connotation of economic characteristics such as factor non-competition and partial exclusivity, increasing returns and diminishing returns, synergy, and externalities. On this basis, Cai Jiming et al. and Zhang Longtian demonstrated the relationship between data elements and value creation and economic growth by using generalized value theory and endogenous economic growth theory respectively.
To give full play to the value of data elements and promote economic growth requires the establishment of a basic data system. Wang Jiandong et al., Tong Nannan et al., and Duan Yaoqing et al. designed and analyzed the basic theory and institutional system of data elements, the property rights system of data elements with Chinese characteristics, and the value orientation of data basic systems. Among them, the market-oriented configuration of data elements is an important mechanism for the value amplification, superposition and multiplication of data elements. Xiong Qiaoqin and others summarized the issues and research related to data transactions. Wei Kai and others summarized the progress, challenges and countermeasures of my country's data element market cultivation. He Jinhai analyzed the practical difficulties of data circulation from the perspective of enterprises. Huang Lihua et al. The product form and transaction mode in the data element market are studied. Regarding the basic issues of the data element market, Shen Weixing, Rong Ke and others discussed the basic theory of data usufruct and the significance of the data classification authorization mechanism. Huang Qianqian and Ouyang Rihui studied the data price generation mechanism and Data valuation and pricing evaluation indicators, Zhou Jianping and others analyzed the impact of privacy computing technology on data circulation models.
The above research provides useful guidance for policy formulation and industrial practice related to data elements. However, the current discussion is not sufficient and in-depth enough to focus on the underlying principle of the value release law of the data elements themselves. The discussion of the value of data elements involved in the above research is more to demonstrate the great role of data elements on other production factors and social and economic production efficiency from the perspective of results and effectiveness. But in what ways does data release its value as a factor of production? In what links does the data element become a new driving force for economic development? These issues are still difficult to clarify, and the exploration of these issues is the grasp of basic laws such as the nature of data elements and the way to release value, and is the theoretical origin for better play of the role of data elements and a sound market system for data elements. Just like the goal of the "Twenty Data" plan, the planning and promotion of the construction of data infrastructure and the cultivation of the data element market must ultimately fully realize the value of data elements and promote the sharing of the dividends of digital economic development by all people. The exploration, discussion, and controversy about the nature of data elements and the basic laws of value release should also become important topics in the study of data elements.
Based on the above background, from the perspective of combining history and reality, analyze the essence and origin of data elements, summarize the ways to release the value of data elements, and propose an exploratory logical framework for the basic laws of the release of data elements value, and strive to promote the follow-up. The in-depth discussion and understanding of the basic concepts and basic mechanisms of the elements will support the research on issues related to the basic system and inspire ideas for solving basic problems.
1 Historical evolution of data becoming a factor of production
1.1 The concept of data and its evolution analysis
The huge role of data has been seen by all. However, the confusion of data concepts has also brought a lot of confusion to related topics such as legal discussion, rights distribution, development and utilization, and has become a stumbling block for industrial digital transformation, digital industrialization development, and digital economy supervision and governance. A clearer and deeper understanding of data is an important prerequisite for grasping the connotation and value of data elements.
In the broadest sense, data are symbols, signals, that record facts, activities. Since data exists in a special form, different scenarios define data differently. In terms of its form of expression, "Ci Hai" (seventh edition) defines data as "the representation of numbers, characters, graphics, sounds, etc. that describe things". According to the definition given in the "Data Security Law of the People's Republic of China", data refers to any record of information in electronic or other ways. For purposes of use, data is defined in the latest edition of the Oxford English Dictionary as "facts or information that are used to form decisions or to discover new knowledge". The descriptions of conventional impressions in dictionaries and laws all show that the essence of data lies not in "numbers", but in the recording and processing of various types of information. Data is an important medium for human beings to understand the world.
In fact, the English data does not have the meaning of "number". Its singular form datum comes from the Latin dare, which means "given something", mainly referring to the facts or basis given in the debate. The household registration registers and astronomical observation records left over from ancient times all conform to people's perception of data today. The uniqueness of data as a cognitive medium lies in that it provides people with the basis for dealing with affairs and understanding the world in the form of a combination system of various symbols gathered according to rules. It is worth noting that the designer of the rule system is a human being, and the dimension of data collection is actually a pre-selected observation perspective. The physical world is mapped to the data world by a specific observation perspective and technical framework. As discussed by the International Data Management Association (DA MA), data needs to be created, and data only makes sense in context or context.
Of course, data and "number" do have a historical relationship. Information recording and processing, and calculation of numerical symbols have always been the basic needs of social operation and development, and they are mutually promoted with the iteration of computing tools and technologies. With the development of computing technology and mathematical theory, by the end of the 18th century, the role of mathematics and statistics in natural science research and social and economic activities continued to emerge. People excavated a large number of causal laws and correlations from numbers and their combinations. Words began to be exclusively used to express raw digital materials that could be processed by mathematics and statistics, and the things they referred to gradually focused on numerical factual records. The person who first translated data into "data" in Chinese has not yet come to a conclusion, but it is certain that data has become more of a numerical symbol in translation. Although numerical values are not the essence of data, after numericalization, powerful tools such as mathematics and statistics can be applied, which greatly improves the value of data. In the current language environment, a symbol table (especially a numerical table) gathered according to rules, a record in the table, or a derived index obtained from the table statistics are all called "data" in different occasions.
With the invention of the computer, in 1946, the word "data" was first used to refer to computer information that could be transmitted and stored. From the superficial meaning, the data processed by the computer refers to a series of binary codes, which are different from data such as symbol tables and conclusive indicators. In fact, binary is a further evolution of numerical symbols. It is a symbol that uses computers to record the world. The recording rules are standardized and normalized at the bottom. At the same time, encoding all kinds of things into binary data that can be processed by computers has greatly improved the ability of human beings to process information and understand the world, as evidenced by the improvement in the application level of semi-structured and unstructured data in the past decade.
It can be seen that human beings' cognition and utilization of data is a process of continuous deepening. In today's big data era, the bottom layer is "big coding", accompanied by "fast processing", which leads to "high value". Based on the above realities, the "data" we talk about today should be defined as: records of phenomena based on binary codes and gathered according to preset rules. "Based on binary coding" excludes non-computer data. If non-computer data is to further exert its value, it also needs to be converted into binary symbols and become computer data. At the same time, this attribute is also inclusive. Images and videos that were once difficult to process have become very popular data, and new things may be added to the category of data in the future. "Aggregation according to pre-set rules" emphasizes that the discovery and creation of data is inseparable from the active design of data collectors, and the rules are the result of the adaptation of data collectors' subjective cognition and objective technical capabilities. Data collectors actively construct a certain aspect of the physical world according to their own needs and conditions, and present these aspects as a large amount of data with precise and controlled rules. The structure and rules of the data set are the external manifestations of the specific perspective of the data collector, and each piece of data in the data set is the basic unit intuitively grasped from the specific perspective. Therefore, the data we are talking about today, although the bottom layer is binary values, the essence of data is not in the value, but in the continuous collection of innovative records and the continuous emergence of cognitive upgrades.
1.2 Socio-economic changes have spawned new factors of production
Factors of production are economic resources used in production and business activities, but not all economic resources are factors of production. Factors of production are not the sum of all the resources put into the production process, but the scientific abstraction of the important resources needed in a certain period of economic development, which is a historical category. In other words, the factors of production are highly condensed costs invested in the production process to obtain economic benefits, and are the basic elements and source of value to maintain the social material production mode. Factors of production such as land, labor, capital, technology, and data are constantly expanding with the development of productivity. The development of productive forces is the decisive force for the development of human society. Under different economic forms, the core elements leading the competition of productive forces are also different. Every change in socio-economic form and industrial innovation is accompanied by the emergence of new factors of production, which lead to a leap in social productivity. Whenever the economic growth rate is faster than the growth rate of known factor inputs, new factors can be abstracted to explain the remaining output that cannot be explained by other factors.
In 1662, William Petty proposed in his book Taxation Theory that "land is the mother of wealth, while labor is the father of wealth and the active factor", thus establishing the dualism of production factors: land and labor. Looking back at the agricultural society, land and labor maintain the survival and development of human society. The two elements together open up the production field based on agriculture, and humans can be separated from the wild nature. Afterwards, after the first industrial revolution and the second industrial revolution, people entered the industrial society. Scholars such as Adam Smith and Alfred Marshall successively put capital, talent, technology, management, etc. Listed as new production factors, these factors have opened up new production fields different from agriculture, which has greatly promoted the progress of human society.
It can be seen that the generalization of new production factors is relatively flexible, and the key is to highlight the value of factors that bring revolutionary improvements to production levels. In 2002, the report of the 16th National Congress of the Communist Party of China proposed "establishing the principle of labor, capital, technology, management and other production factors participating in the distribution according to their contributions", and in 2013 the Third Plenary Session of the 18th CPC Central Committee proposed "improving capital, knowledge, technology, management In 2015, the Fifth Plenary Session of the 18th CPC Central Committee proposed to "optimize the allocation of labor, capital, land, technology, management and other factors", and in 2019 the Fourth Plenary Session of the 19th CPC Central Committee proposed "to improve A mechanism in which production factors such as labor, capital, land, knowledge, technology, management, and data are evaluated by the market and rewards are determined according to their contributions.” The listed factors of production are always developing, which fully reflects the epochal nature of the factors of production, and the focus of attention on the factors of production should be placed on the most productive aspects of the era. The key to condensing the factors of production is to highlight the aspects of things that can be put into production in the corresponding era, conceal the other ways of survival of the things, and give full play to their value in promoting industrial development and economic growth.
Today's digital economy is the main economic form after the agricultural economy and industrial economy. With its rapid development, wide range of radiation and unprecedented influence, the digital economy is becoming a key force for reorganizing global factor resources, reshaping the global economic structure, and changing the global competitive landscape. Under the background of rapid iteration of digital technology and extensive digitalization of the whole society, data has the characteristics of large scale and high value, which has comprehensively changed human production, circulation, distribution, consumption activities and economic operation mechanisms, social lifestyles, and national Governance model. Similar to the role of production factors during the agricultural revolution and industrial revolution, data gradually opened up new production fields that are different from industry and even independent of the real world. Data has become a reserved resource for production purposes, providing the foundation and possibility for the continued growth and sustainable development of the digital economy, and gradually becoming a key factor of production in the era of the digital economy.
1.3 Data has become a key factor of production in the digital economy
As discussed above, the reason for condensing data into production factors is that it has shown outstanding value in promoting the development of productivity, and this process has a profound technical and industrial background. After the invention of the computer and before the birth of the database, programmers processed data for the underlying files of the operating system, with complex operations and low efficiency. In 1970, Edgar Frank Codd (Edgar Frank Codd) proposed the relational database model, and then the wide application of SQL language and online transaction processing (on-line transaction processing, OLTP) system gave full play to the relational database model. The value of the database, data users can use standardized tools to operate data, focus on the development of upper-level applications, and significantly improve the efficiency of business operations. At the end of the 20th century, the Internet entered the stage of large-scale commercial use, and the characteristics of networking gradually became prominent. With the expansion of data volume, the concept and technology of data warehouse are gradually perfected, and the subsequent demand for data value mining is also increasing. Edgar Frank Kodd further proposed online analytical processing to support complex analysis operations in 1993 (on-line analytic processing, OLAP) system, the barriers between businesses began to break through, and the role of data-driven analysis and decision-making in production gradually emerged. In recent years, with the exponential growth of data volume, big data components such as Hadoop, Spark, and Flink, as well as emerging technologies such as cloud computing, artificial intelligence, and deep learning, have also shown a trend of industrial development, rapid iteration, and deep integration. It has entered an intelligent stage characterized by in-depth data mining and fusion applications. The real-time processing and intelligent analysis of massive data has greatly promoted the improvement of production efficiency. Data has become an irreplaceable basic element and source of value in the production process.
It can be seen that "data element" refers to "data" in the context of productivity and production relations in the era of digital economy under the background of big data technology and industry, and it emphasizes the value of data to promote production. As a term from a theoretical perspective, from a static point of view, the extension of data elements refers to product data, equipment data, industrial data, agricultural data, financial data, logistics data, social data, consumer data, and public data operated by various industries. In production and business activities, these data types are processed into various forms according to production needs. Summarized as the connotation at the theoretical level, data elements are: computer data and its derivative forms that are gathered, sorted, and processed according to specific production needs, and participate in social production and business activities.
Based on the above definitions, original data sets, standardized data sets, various data products, and data-based systems, information, and knowledge that are put into production can be included in the discussion of data elements. From the business system of raw data input and output, to the interface query of financial institutions to personal credit information systems, to the related services of enterprise credit data mining, to data application terminals, and data reports, various industrial practices have seen a situation where production efficiency has been comprehensively improved. , where data is put into production in various forms, releasing new value.
Therefore, from the perspective of industrial practice development, it should be emphasized that the data element is a new economic kinetic energy rather than the purpose itself. It can change dynamically with the context. What needs to be highlighted is its production value, and it is not necessary to specifically frame which one is A data element, which piece is not a data element. For example, although a portrait photo taken by a digital camera is a binary-coded image, it is a copyrighted photographic work rather than a data element for the photographer. However, if this photo becomes one of the face recognition data sets, it has the value of data elements. As another example, the International Data Management Association believes that data is a form of information, information is also a form of data, and both data and information need to be managed. Therefore, data elements can include the entire industrial chain, raw data sets that are put into production and create value in the industrial ecology, standardized data sets, data service terminals, data interfaces, data models, data scoring, joint computing, business systems, data reports, etc. For each form, the corresponding business format needs to clarify the red line of supervision and encourage innovation and development.
Gao Fuping's definition of artificial data elements is "as a factor of production in the era of digital economy, data is not information in the traditional sense, let alone digital knowledge achievements, but generally refers to information generated in intelligent network systems for machine learning, etc. Machine-readable raw data used by intelligent analysis tools”; Wang Chaoxian and others proposed that the form of data elements that create value is information and knowledge, and the essence is to optimize decision-making under uncertain conditions. These perspectives profoundly reveal the role of data elements in production to release value by improving the level of cognition and intelligence. However, it should be noted that more and more production activities are currently shifting from the physical world to the data world, and even many production activities must be completed in the data world, and the concept of data elements also contains more connotations. Data elements are based on the core of the concept of data, relying on diversified technical support, so that the multi-level role played by data in history can be integrated in the contemporary era to realize the release of its value.
2 Three Value Releases of Data Elements
The above discussion shows that data is not a factor of production from birth. In the past 20 years, the ability of human beings to collect and process data has made a qualitative leap, and the digital transformation of economic activities has accelerated. Data has gradually become a factor of production, and its multiplier effect on improving production efficiency has become prominent. The fundamental purpose of activating data elements is to put them into production in a diverse and innovative way, so as to create greater value for economic and social production. Exactly how data elements exert their value as production factors needs further analysis. With the development of information technology and the evolution of industrial applications, the way data elements are put into production can be divided into three value release processes, namely, data supports business integration, data promotes digital intelligent decision-making, and data circulation empowers externally, as shown in Figure 1. It should be noted that the reason why these three values are three ways to release the value of data elements is because on the one hand, there is a progressive relationship between these three values, and the latter is often based on the former; There is a juxtaposed relationship among the three pathways, and these values can and must be paid attention to and fully released at the same time.
Figure 1 Three value releases of data elements
2.1 One-time value: Data supports business integration
The primary value of data input into production is reflected in supporting the operation of the business systems of organizations such as governments and enterprises, and realizing the connection between businesses. First of all, data is generated through the design of various business systems, and through the specification of business systems, the continuous accumulation of standardized data within a specific range is gradually gathered into available resources. Secondly, these data support the normal operation of the business system. Through the computer's reading and writing of data, the initial standardization, automatic management and operation of the business are realized. Finally, a certain degree of standardized data has universality, and the data can break the boundaries between offline and online, break the boundaries between business processes, and even have the ability to break the boundaries between business areas within the organization. In short, when the business system is set up and the data is running in the system, the data has already released value in production activities.
From the point of view of the implementation link of putting into production, the intuitive performance of data-supported business integration is to improve the utilization rate of production factors such as labor. The technical elements are similar. By putting technology into the production link, the replacement of part of the labor and positions in the business process can be realized, and its multiplier effect can be played. In this sense, just like putting technology into production to release value, the first job to play the role of data elements is to fully understand the role of data elements, and truly use data in business and penetrate business. At this time, the data is generated centrally and stored in a single unit with the business system, and the corresponding governance work is mainly based on conventional database management such as adding, deleting, modifying, checking, aligning, and merging, and mostly focuses on process improvement and Interconnection of relevant business data. Although the data has not been deeply integrated and analyzed at this stage, whether it is developing system to accumulate data, operating data to standardize business processes, or using data to connect businesses, they are all production activities in the data world and create corresponding value. Therefore, the primary value of data is the first step to realize digital transformation and improve the efficiency of internal operation and management of the organization.
In order to promote the value release of data, the main focus of the government, enterprises and other organizations is business data and the construction of various business information systems. For example, 20 years ago, my country's e-government construction represented by the "Two Networks, One Station, Four Databases, and Twelve Funds" project was in full swing. After years of promotion, the construction and application of government business information systems at all levels have achieved remarkable results. The way of digitalization has realized the effective operation and connection of data in the system, and the level of public services has been comprehensively improved, laying the foundation for today's digital government construction. At this stage, the types of data held within the organization are relatively single, the calculation requirements are simple, and the technical threshold is low. The key is to dig deep into business needs and clarify the direction of business data. At present, there are still a large number of industries and enterprises that have failed to effectively realize digital transformation. The traditional working mode of "running the process and asking questions" hinders the improvement of production efficiency.
In short, the primary value of data elements is like finding mines and accumulating mineral deposits, which is the basic work of the circulation of data elements. In the context of the fact that many industries and enterprises do not yet have the ability to digitize their businesses, it is too early to talk about the data element market for these industries and enterprises. To better play the role of data elements, it is necessary to help these industries and enterprises release the primary value of data elements and use data to support business integration. With the mining of business needs and the construction of business information systems, a large amount of valuable business data continues to accumulate. The situation of independent storage of business system data and high barriers to sharing within the organization no longer meets the needs of production and operation development. Data is managed in a unified manner and used throughout Scenarios continue to emerge, laying an important foundation for further mining the value of production factors of data.
2.2 Secondary value: Data promotes digital decision-making
The secondary value release of data elements put into production is reflected in revealing deeper relationships and laws through data processing, analysis, and modeling, making decisions in production, operation, service, and governance more intelligent, smarter, and more accurate. . On the one hand, through the management and analysis of a large amount of data, the decision makers within the organization can realize "use data to speak and use data to make decisions", use the key indicators and information presented by the data to evaluate the development trend, effectively prevent and resolve risks in real time, and innovate Action strategy; on the other hand, data analysis is directly embedded in the system and closely integrated with the business, and real-time data mining, classification, prediction, clustering, etc. directly endow the business with intelligent value.
In both aspects, data creates production value by bringing new information and upgrading the cognitive level. From the perspective of cybernetics, matter, energy and information are the three cornerstones of the world, and information is neither matter nor energy. Just as the land element is the material basis of all production and management activities, the capital element improves the efficiency of material exchange, the labor element and technology element promote the transfer and transformation of energy, and the data element can support the creation and transformation of the cornerstone of information. Compared with other elements, the grasp and application of information is the unique point of releasing the value of data elements. In the secondary value of data elements, the term "decision-making" has a broad meaning, including not only human choices and decisions, but also what the industry calls "intelligent decision-making" by machines. Both humans and machines can make choices based on various information, laws, and rules. Humans can use data to better understand the situation and laws, and business rules that are difficult for humans to recognize can be handed over to machines. Fundamentally speaking, the secondary value release of data is a cognitive breakthrough brought about by the mining of deep relationships and laws. artificial limitations.
At present, some leading manufacturing companies have established a complete data chain for business management and business decision-making, and some key business management decision-making actions can be replaced by data, so as to optimize the employment structure of management positions through business intelligence; major banks fully Integrate the business data of small and medium-sized enterprises, mine more accurate corporate customer portraits and credit scores, and then determine the risk assessment results of small and medium-sized enterprises' loans, providing the possibility of low-cost financing for small and medium-sized enterprises. It can be seen that data elements can not only be put into their own business to support analysis and decision-making, but also can be integrated with other production elements to form new element combinations and element structures. Data-driven intelligent and intelligent decision-making can achieve more material wealth and services with less investment in factor resources through the business combination of traditional factors of production, thereby optimizing the operation and allocation of traditional production factors and making traditional factors Double the value, improve the efficiency of total factor production, realize a leap in productivity, optimize the industrial chain and reshape competitiveness.
In short, the secondary value of data elements has uniqueness that other production elements do not have, and is the core of the value release of data elements. The important goal of the circulation of data elements is also to give back the release of secondary value, so that the value of data at the cognitive decision-making level can benefit the majority of subjects. Therefore, the foundation of the secondary value of data elements must also be firmly established. In order to promote the release of the secondary value of data elements, organizations need to actively improve data awareness and data mining capabilities, and with the assistance of data analysis, artificial intelligence and other technologies, build a new production system for data automation, intelligent collection, processing, and execution. Eliminate human cognitive misunderstandings and subjective biases, and give full play to the key role of data elements in productivity competition. Strategic decision makers can combine their deep understanding of business goals and use the results presented by massive data mining to make smarter decisions. The executive layer can make full use of data analysis results to allow people to make more effective choices through intelligent associations and graphs. , let the machine find key functions, tags, and portraits, realize automatic prediction and analysis, make the secondary value of data give back to the primary value, and make business operations more intelligent.
2.3 Three Values: External Empowerment of Data Circulation
The three value releases of data elements put into production enable data to be circulated to places where it is needed more, and high-quality data from different sources can be converged and integrated in new business needs and scenarios to achieve win-win and multi-win value utilization. Circulation empowerment is a key to the value leap of data elements. On the one hand, data has an increasing return to scale effect. The larger the scale and the more multi-dimensional data fusion and aggregation, the greater the value created. Various matters in economic activities such as finance, logistics, communications, and automobiles can be assigned by data from multiple sources. Yes, the full integration of enterprise-owned data and external data can maximize the value of data applications. Therefore, with the release of the primary value and secondary value of data, the demand for data by organizations has exceeded the data generated by themselves. On the other hand, at this stage, a large amount of data is concentrated in a small number of subjects, and the problems of uneven distribution of data elements and structural imbalance are more prominent. The low-cost replicability of data can change the structure of input factors into production. Larger-scale and wider use of data elements will not increase too much additional cost, but it can generate excess profits and increase social welfare [28]. The "Data Twenty" emphasizes promoting the sharing of the dividends of digital economy development by all people, and the circulation of data elements can stimulate the positive externalities of data, so that the value of data can benefit the majority of market entities and all people.
Historical experience shows that production factors do not necessarily need circulation, but circulation helps to further release the value of production factors. In the field of agriculture, land elements have released the value of food production since ancient times. The reform and implementation of the land transfer policy have enabled the effective transfer of land between the supply side and the demand side, further promoting farmers' increase in property income, and activating the transfer of surplus agricultural labor. Referring to the transfer experience of land elements, combined with the attributes of data elements themselves, the three value releases of data elements require organizations to effectively manage their own data, improve the ability to supply high-quality data, and tap the demand for external data introduction. There is a relationship of opposites and unity between demand and supply, and organizations and related service providers need to pay attention to the improvement of diversified capabilities. In a data circulation process, although the data supplier and the demander are not the same subject, a subject can have both the identities of the data supplier and the demander, and perform conversions in different business scenarios. Under the regulation of market spontaneous means in pursuit of interests, demand can drive supply, and supply can also create demand. In the process of aligning the data frameworks of the supply side and the demand side, the corresponding market scale is continuously expanded and new economic growth points are added, so as to continuously release the business value, economic value and social value of data elements in multiple scenarios.
In order to achieve efficient and standardized matching between data supply and demand, the cultivation of the data element market has gradually become the focus of the industry. The basic meaning of the market is a place where all parties freely participate in the exchange under the consensus protocol. The data element market is a complex system supported by a series of systems and technologies, with data suppliers and demanders as the main body, various forms of data as the object, and circulation as the means to realize the respective demands of the participants. , Business requirements, circulation models, rights relations, price mechanisms, technical conditions, supporting facilities, etc. are all elements of the data element market. Therefore, the cultivation of the data element market should be encouraged and regulated based on the principles of free flow and inclusive development under the premise of ensuring security and privacy, so that various tasks can strongly support the full release of the value of data elements.
3 Conclusion
Promoting the development of data elements is a profound grasp of today's technology and industrial background, and a key measure to seize the commanding heights of international competition in the digital economy era. The development of data elements should focus on releasing the value of data elements. The law of three value releases of data elements highlights the mechanism of action of the data elements themselves, and to a certain extent reveals the relationship between the development of data business within the organization and the productivity improvement of the whole society. The basic laws of data elements and their value release still need to be continuously in-depth excavated and explained, but the three values of data elements remind people: the development of data elements is a systematic project, which involves both the data application within the organization and the general society of the whole society. benefit development; it involves both the allocation of data resources and the role of data in allocating other resources. It should be emphasized that although data can achieve value-added and leap in circulation, it does not mean that it has completely entered the stage of tertiary value. Some organizations still have a vague perception of data applications, and are limited by insufficient funds, talents, and technical levels. The data chain covering the entire process of production activities and the entire industry chain is still not perfect, and it does not yet have electronic business data or intelligent analysis and decision-making. Ability. Under such conditions, such organizations cannot effectively utilize external data even if they introduce external data, and cannot form a value loop that contributes back to business development. Therefore, the development of data elements needs to be promoted in an overall manner, and the primary value and secondary value still need to be continuously released. On the basis of wider business integration and digital decision-making, the value of external empowerment of data circulation should be fully utilized.
About the Author
Wang Zeyu (1996-), male, engineer at the Institute of Cloud Computing and Big Data, China Academy of Information and Communications Technology. His main research direction is data elements and data circulation.
Lu Ailin (1995-), female, engineer at the Institute of Cloud Computing and Big Data, China Academy of Information and Communications Technology, her main research direction is data elements and data circulation.
Yan Shu (1989-), male, Ph.D., deputy director and senior engineer of the Big Data and Blockchain Department of the Institute of Cloud Computing and Big Data, China Academy of Information and Communications Technology. His main research directions are data elements and data circulation.
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http://www.infocomm-journal.com/bdr
http://www.j-bigdataresearch.com.cn/
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Big Data Journal
The bimonthly "Big Data Research (BDR)" is a journal published by Beijing Xintong Media Co., Ltd. , has been successfully selected into the core journals of China's science and technology, the journal of the China Computer Federation, the Chinese science and technology journals recommended by the China Computer Federation, the classified catalog of high-quality scientific and technological journals in the field of information and communication, and the classified catalog of high-quality scientific and technological journals in the field of computing, and has been rated as the National Science and Technology Journal for many times. The most popular journal in the discipline of "Comprehensive Humanities and Social Sciences" in the academic journal database of the Philosophy and Social Sciences Documentation Center.
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