[author]Ma Yanxin
[content]
Ma Yanxin
Researcher, South China Normal University School of Law
Keyword：Public Data; Authorized Operation; Government Procurement; Franchising;
Data resources hold enormous potential for social, economic and political value, and public data are a particularly important part of data resources because of their large quantity, high quality and relatively uniform standards. In order to further realise the effective supply of public data, the 14th Five-Year Plan proposed for the first time to "carry out pilot projects of government data authorisation and operation, and encourage third parties to deepen the mining and utilisation of public data".
At present, the practical exploration of the authorised operation of public data is advancing rapidly, and the demand for system provision is particularly urgent, with many theoretical and practical issues to be resolved, such as what exactly is the authorised operation of public data? What is its legal nature and legal application? What types are included? How to develop specific systems such as application scenarios and target setting, fee collection, revenue distribution, subject access, and supervision? How to balance the public interest and operation? How to protect and realise the public interest? This is the topic to be discussed in this paper.
1 The current situation and challenges of public data authorisation and operation
1.1 Practical Exploration of Public Data Authorised Operation
At the normative level, there are no laws and regulations at the central level to provide for the authorised operation of public data, but through the "14th Five-Year Plan for the Development of the Digital Economy" and other policy documents to encourage and guide the innovative exploration of the authorised operation of public data. At the local level, some provinces and municipalities have actively explored the institutional construction of public data authorisation and operation, and some legislation has been formed. 2021 The Shanghai Data Regulations for the first time provided for public data authorisation and operation, stating that the purpose of public data authorisation and operation is to improve the level of socialised development and utilisation of public data, and that authorised operating entities should, within the scope of the authorisation, carry out the development and utilisation of data, as well as the provision of data products and services. Although the Zhejiang Provincial Public Data Regulations adopted in 2022 does not contain a specific section on the authorised operation of public data, Article 35 clearly states that "the authorised operating unit shall rely on the public data platform to process the public data authorised for operation; and the data products and services formed by the processing can be provided to the users to obtain a reasonable income. The authorised operating unit shall not provide the original public data of the authorised operation to a third party". This is the most clear and detailed provision on the authorised operation of public data in the existing local legislation.
In terms of organisational structure, the current dominant mode of public data authorisation and operation is the organisational system of "one bureau, one centre and one company". The "bureau" refers to the local big data bureau or government data management bureau, the "centre" refers to all kinds of big data centres, and the "company" includes all kinds of market players. The "bureau" is the regulatory body, the "centre" is the operational body, and the "company" is the entity that actually undertakes the operational business.
In terms of application modes, the authorised operation of public data at this stage generally revolves around specific industries, specific regions or specific application scenarios. Key industries include finance, transportation, medical care, etc. For example, Beijing Municipality authorised the Beijing Financial Big Data Company to gather multi-dimensional data on industry and commerce, justice, taxation, social security, provident fund, real estate, etc. that are "urgently needed and specially required" by financial institutions to carry out credit business, so as to satisfy the needs of financial institutions for credit collection services before, during and after loans; the regional representative is the The regional representative is the Greater Bay Area Data Centre, which focuses on promoting regional data integration and realising cross-regional applications for regional integration; representative scenarios include epidemic prevention and control, trade at ports, and so on.
At present, the practical development of public data authorisation and operation is still in the exploratory stage, with rich forms and many changes in specific contents. However, combining the existing legal norms, organisational structure and application models, a descriptive definition of public data authorisation and operation can be formed: public data authorisation and operation refers to the development and use of public data for the purpose of authorising specific operating bodies by the authorities to process the public data, so as to form data products and services provided to the market and society.
1.2 Theoretical Foundations of Authorised Operation of Public Data
1.2.1 Institutional value of public data authorisation and operation
The core of public data authorised operation is to solve the problem of insufficient supply of public data elements. Traditionally, the main channel for supplying public data to society is the public data opening system, which provides data directly to the public as users. In recent years, the opening of public data has achieved many results, such as a large increase in the number of open data platforms, but the quality and quantity are still very unsatisfactory, and there is even a paradox that "the data opened by the government are useless, and the data needed by society are not open by the government". There are two core reasons for this, one is the security risk of public data opening, and the other is the lack of direct incentives for data opening. For the government, the more valuable data, the more sensitive, the more likely to produce security risks. If there is a lack of direct incentives, the government will minimise the substantive opening of public data in order to prevent security liabilities.
Public data licensing operations, as a new type of public data supply channel, can alleviate or even solve this dilemma. On the one hand, in public data authorised operation, those who have direct access to the raw data are the operating entities with access thresholds, while the public and other users use data products and data services without direct access to the full sample of raw data. This is more convenient for security supervision, and the data can be "available but not visible" through multi-party security calculations and other means. On the other hand, data authorised operations treat public data as a value-added public resource that can bring certain benefits to the government, which provides incentives for the government to supply public data and encourages the government to supply data more actively.
1.2.2 Justification Basis and Doubts of Public Data Authorised Operation
The essence of the aforementioned economic incentives is the operational utilisation of public data. Both theory and practice do not completely exclude government operational behaviour, especially since China, as a publicly owned country, possesses a large amount of natural resources, state-owned enterprises and other public property, and has the right and duty to operate these public properties to promote the preservation and appreciation of the value of state-owned property. It is reasonable for the government to authorise the operation of public data as "public resources" to carry out corresponding business activities.
However, a major difference between government operation and enterprise operation is that government operation is not for the government's self-interest, but to increase the wealth owned by the whole nation and realise the corresponding economic regulation function through the operation. Therefore, even if the public-private partnership, operational and other ways, the government can not completely copy the private sector management, its behaviour must reflect the "public nature", based on public values as the basis of behaviour. The operational nature of the government's business behaviour is essentially a specific way of realising the public interest, and ultimately to realise the public interest and public value.
Although there is no contradiction between public interest and operation in essence, specifically on public data supply, many scholars have raised concerns about the potential conflict between the two, that is, the economic incentives of the authorised operation of public data may, in turn, crowd out the space of general public data openness, and the administrative authorities may, for the sake of economic interests, reduce the public interest of general openness, and turn to strengthen the administrative monopoly, and ultimately damage the public interest that should be safeguarded.
At this point, it is necessary to analyse the principle of proportionality for the authorised operation of public data, take the ultimate realisation of the public interest as the administrative goal, compare the appropriateness and necessity of various options, and further explore what benefits are gained from the authorised operation of public data, which of them are the direct economic benefits of the government, which are the social benefits including positive economic externalities, and whether these benefits are sufficient to outweigh the costs as well as the crowding out of the social opportunities brought by general openness. the loss of social opportunity from universal openness. This paradoxical balance between public goods and operations will also constitute an important clue in the construction of a public data regime.
1.2.3 Institutional Challenges of the Public Data Authorisation System
Currently, academics have devoted a lot of attention to the authorised operation of public data, and a series of results have been formed, including the basic mechanism and mechanism of the authorised operation of public data. Most of them believe that government data authorised operation is essentially a kind of franchising, and it is appropriate to regulate it according to the logic of infrastructure franchising, and then put forward specific suggestions such as adopting the "operation + maintenance" model.
These results are quite inspiring from many perspectives, but it is difficult to completely reflect the whole picture of the public data authorisation and operation system, resulting in many internal conflicts that are difficult to be resolved in the system. This is largely due to the fact that what we now call "public data authorisation and operation" is not a single system, but a mixture of many systems of different natures.
For example, in terms of the type of data being operated, the nature of the system for authorising the operation of different types of data is not exactly the same. According to the type of openness, public data can be divided into three types: unconditional openness, conditional openness, and prohibited openness. Generally speaking, in addition to the prohibition of open public data shall not be authorised to operate, the rest of the unconditional open data and conditional open data can be categorised as "public data authorised to operate", but there is actually a fundamental difference between the two "authorised to operate". In the case of conditionally open public data, the opening is conditional. In other words, it is prohibited in general, and will be opened only after the administrative subject has granted a conditional licence, and there is indeed the possibility of "authorisation" in between. Whether this authorisation is a licence or a concession will be further explored later in this paper. But unconditional open class of public data is different, it should be unconditionally open to the whole society, this time the "authorisation" is necessary? On the other hand, the operating body to use the government unconditionally open public data, development and formation of data products and services to obtain income, which is a normal market behaviour, also often in the legislative norms have been recognised, the operation of this type of data, whether it is still necessary to authorise a specific administrative organ?
In addition, from the perspective of specific systems such as charging, there is also a big difference within the system of authorising the operation of public data. The issue of charging is at the core of public data authorisation and operation, both as the basis for the motivation of exploitation and as the focus of public concern. Fees include two levels of meaning, the government's fees for the authorised operating body and the authorised operating body's fees for the society. According to the aforementioned definition of authorised operation of public data, in terms of the relationship between the government and enterprises, what is now called authorised operation includes both the entrusted operation of unconditional open class public data that the government pays the enterprise to entrust the enterprise with, as well as the licensed operation of the enterprise that pays the government to obtain the concessionary operating right of the data; and in terms of the relationship between the enterprise and the society, the existing system also includes the free of charge, costly charge, market-based charge, and so on.
Although different types of public data licensing operations are often lumped together in practice, their institutional connotations, nature, objectives and even the legal rules that should be applied may not be exactly the same. And there are potential contradictions between these different types of systems in terms of their basic objectives and value orientations, thus further triggering inherent conflicts in the systems. For example, the value-added use of public data implies a contradiction between the special use of public data by specific subjects and the equal use by the public, as well as a contradiction between the value-added use of public data by a public data management agency and its impartial performance of its public data management duties, and the authorisation of the operation of which may lead to the mixing of governmental roles and intermingling of functions, which should be appropriately functionally differentiated.
Therefore, in order to clarify the complicated practical reality of authorised operation of public data, resolve or alleviate the conflicts between public welfare and operation, different government functions, special use and general use, and establish a clear and effective institutional mechanism, it is necessary to construct a typology of the authorised operation system of public data, and carry out a refined study of the legal nature, specific system and other issues on the basis of the typology.
2 Types of public data authorisation and operation models
2.1 Starting point of the typology of public data authorisation and operation
No matter how rich the institutional connotation of public data authorised operation is, there are some common foundations that are clear, namely, public data authorised operation is a public-private cooperation model with the administrative subject as the data provider, the operational subject as the data processing and processing party, and the social subject as the end-user of data products and services. This contains three sets of relationships between the government and society, the government and the operating subject, and the operating subject and society. The government-society relationship is the foundation, depending on the government's functions, and is related to the value conflict of the authorised operation of public data; the relationship between the government and the operating body is the key to PPP, defines the core framework of the overall system, and determines the different natures of the authorised operation of public data; and the government performs its functions to the society through the operating body; after clarifying the relationship between the first two, the third set of relationships will be clear, and the relevant concrete system will also be gradually clear. Therefore, from the perspective of basic typology, what needs to be clarified is actually two questions: what are the functions of the government in the authorised operation of public data (government-society relationship)? What kind of public-private partnership (PPP) model should be adopted (government-operator relationship)?
2.1.1 Government Functions
In the authorised operation of public data, there are two functions of the government, namely the public service function in the narrow sense and the public asset value-added function, which are based on different administrative purposes and require the adoption of different public-private partnership (PPP) modes, thus creating a series of distinctions in the type of data to be applied, the relationship between the government and the operating entity, and the system of charging the society.
Broadly speaking, the modern government has undergone a transformation from a management-based government to a service-based government, and all functions can be collectively referred to as public services, which in the broad sense include basic public services and non-basic public services. The public service function in the narrow sense referred to in this paper refers to the function of the government to make citizens' specific direct needs satisfied in a certain way, excluding the government's functions of economic regulation, market supervision, social management and so on. In public data authorisation and operation activities, the government's narrow public service function focuses on the universal openness of public data, pursues the public's equal, fair and universal access to and use of public data, and safeguards the public nature of public data.
Under the narrow public service function, the administrative purpose of the government is to directly satisfy the social demand for data, and it should open up public data to the greatest extent possible, with unconditional openness of public data as the main focus. For those that cannot be opened unconditionally due to security reasons, the scope of restrictions and conditions should be clearly defined. If the public meets the conditions of use, the application can be reviewed by the administrative organ. Conditional openness at this time is actually a kind of general licence or "control licence", which lifts the general restriction on the freedom of a certain activity because of the need for preventive control.
In contrast, there is the value-added function of public assets. The property attributes of public data are still highly controversial, but they can at least be considered a "public resource". There is also the possibility that public data under direct government control can be converted from a public resource to a public asset. As a public asset, the government is obliged to develop and utilise it to preserve and increase its value, thus creating the function of adding value to public assets. This function focuses on the value-added development of public data, aiming at maximising the value of public data, transforming data as a production factor into diversified data products and services, and pursuing the value-addedness of public data. With reference to the general theory of public resources or public utility concession, if the public data is set up "audit" or "authorisation", its essence is a "concession", that is, the administrative authorities based on the ownership of resources or monopoly. This is the act of transferring the right to develop, use or operate resources to a specific subject based on the organ's ownership or monopoly of the resources, and it is generally believed that such transfer should be paid.
2.1.2 Public-Private Partnership
Traditional public law theory holds that it is the legal obligation of the government to provide public services in the broad sense. However, with the continuous expansion of the government's public service functions, it inevitably leads to an increase in operating costs and financial pressure, and the contradiction between the supply of and demand for public services becomes more and more prominent. It has become a trend for the government to introduce social forces to fulfil administrative tasks through various types of public-private partnerships (PPPs).
The choice of public-private co-operation methods depends on the different administrative tasks, and it is possible to distinguish all administrative tasks into transactional business and operational business. Business operations refer to those public service operations that are provided by the government free of charge or at cost only, and the scope of business involves: basic public service operations aiming at satisfying basic human needs, social public services aiming at satisfying social needs, and organ services aiming at satisfying organ services, and so on. Traditionally, such services were mainly provided by the government or various types of government-established institutions, but nowadays it has become more feasible or better to provide public services in the form of privatisation or return to market value, which has led to the development of public-private partnerships (PPPs), such as government purchasing and public service outsourcing. PPPs for such operations are usually realised through general government procurement of services.
Operational businesses refer to those that go beyond the basic needs of safety and order, have strong economic benefits, and can realise the goal of value-added or value-preservation of public assets, and mainly include basic industries, infrastructure construction, and municipal public utilities. The entrusted operation of this type of business is usually premised on the granting of franchises by the government, and the operator recovers its investment or costs by charging the users, and its public-private co-operation usually adopts the franchising method.
2.2 Summary of Public Data Licensing Models
In public data licensing operations, the above two choices of public-private partnerships correspond to the different focuses of government functions, and the initial typology of public data licensing operations is thus completed. This paper summarises them as the government procurement service model and the franchising model according to their institutional characteristics.
2.2.1 The Basic Form of Government Procurement Models
In order to realise the government's public service function in the narrow sense, administrative entities can carry out public-private partnerships by means of utility business outsourcing. This public-private partnership has obvious characteristics of public welfare and universality, and weak market factors, so it is difficult and should not be possible for enterprises to make profits through user fees. In order to achieve public-private partnership, the basic economic model is that the government pays for the procurement of the enterprise's services, giving full play to the enterprise's advantages in organisation and technology, reducing costs and increasing efficiency, and providing a better quality of service to the relative.
In the process of promoting the reform and construction of digital government around the world, there has been the practice of the government procuring services from specialised construction and operation entities. The organisational structure is as follows: a professional construction and operation centre is set up, the competent authorities in charge of the construction of the "digital government" coordinate and integrate the government's needs, and purchase services from the operation centre in a unified manner, while the business departments use and evaluate the services provided by the operation centre. There are two main ways for the government to purchase public data services: first, partial outsourcing, where the government is responsible for supervising the implementation of the contract between the two parties and pays the contractor according to the quality and quantity of the services provided by the contractor; and second, entrusting agency, where the public data infrastructure is entrusted to the contractor to operate by means of public tender, and the government supervises and inspects its operation and pays the contractor according to the quantity and quality of the services and the quantity of the services stipulated in the contract.
2.2.2 The Basic Form of Concession Mode
For the government's function of adding value to public assets, the concept of "adding value" itself implies carrying out activities with a certain degree of operation under the market evaluation mechanism. In operational activities, there is room for value-added public assets, which means that the operator in a public-private partnership (PPP) can benefit from the operational activities themselves, rather than being paid by the government. This gives rise to the franchise model, which is different from the traditional government procurement model. Broadly speaking, franchising is also a form of government procurement in which the government awards a franchise instead of paying a direct price. In the franchising model, the government grants the operator the right to franchise specific public data and the corresponding revenue rights, and the operator processes the public data to form data products and data services for the community. Also providing data products and services, the franchising model places more emphasis on efficiency and marketability than the government procurement model, and has a stronger economic incentive effect.
2.2.3 Further classification under the two models
The basic forms of the two aforementioned models are typical general patterns, and there are some cross patterns in practice, for example, under some government procurement models, the government also wants to further handle and process public data to realise the value-added of the data; and under many franchising models, the provision of standard-compliant public services is also a functional requirement of the government. Therefore, further classification can be carried out to clarify the applicable scenarios and reflect the balance and inclination of different functional focuses in the system design, so as to achieve a more refined system construction by targeting the development of specific systems such as target setting, charging, revenue distribution, access and supervision. This further classification can start from the two dimensions of risk and value of data, which will be further discussed in the model selection section of this paper.
2.3 Legal Nature and Legal Application of the Two Major Models
Depending on the source of funding and the legal relationship, PPPs can be differentiated into commissioning and franchising models. In the commissioning model, the operator performs tasks and provides services, and obtains the relevant fees directly from the administrative subject, and usually the user does not pay or only pays costly fees. At the same time, the user and the administrative agent, although intermediated by the operator, still constitute a more direct legal relationship, with the administrative agent in many cases assuming direct responsibility. In the concession model, the user pays in most cases and the Government provides no or only partial funding. The operator is self-financing under the concession model. There is no direct legal relationship between the administrative entity and the user, but rather a secured indirect liability.
The government procurement model is a typical commissioning model, and the legal nature of this commissioning model is administrative commissioning, and the "authorised operation" at this time is a kind of "commissioned operation", which can maximally retain the government's dominance in the public-private partnership of public services, and the government is the manager and operator of public data and resources, and the government is the manager and operator of public data. The government is the manager and operator of public data resources, and has the responsibility to supervise the whole process of authorised operation. Even if the operation of data is entrusted to a third party in the form of purchasing services, the authorised person has to bear the responsibility for the operation of public data externally. In order to provide public services in the narrow sense, there is also a strong justification for the costs to be borne by the public finance as a whole. According to Article 2 of China's Government Procurement Law, "Government procurement refers to the act of state organs, institutions and organisations at all levels of government, using financial funds to procure goods, works and services within the centralised procurement catalogue formulated in accordance with the law, or above the standard of the procurement limit". The government's procurement of data services can be regulated under the systematic framework of the Government Procurement Law.
Under the franchise model, the government's value-added function of public assets is realised through public-private partnership in the franchise mode of business operation, where the "authorised operation" grants the "franchise right". Existing laws and regulations do not explicitly include public data in the scope of infrastructure and public utility franchising, and this paper will discuss in the next section what public data can be justified for inclusion in the scope of franchising. The existing public data franchising model can be based on Article 12(2) of the Administrative Licensing Law, which states that administrative agencies may establish franchises for "the exploitation of limited natural resources, the allocation of public resources, and the market access of specific industries directly related to the public interest, etc., which require the granting of specific rights". The public data franchise model can refer to some mature experiences of the franchise system in the "Measures for the Administration of Infrastructure and Public Utility Franchising" and other regulations.
3 Selection of Different Models for Public Data Licensing
Clarifying the application scenarios of different models is especially crucial for the public data authorisation and operation system, which can help to solve some of the difficulties in the development and utilisation of public data in practice. One of the challenges is the lack of incentive to develop, which is particularly prominent in the government procurement model. Under this model, the development and utilisation of public data is a function of the administrative authorities, which need to bear the relevant costs, risks and responsibilities, but it is difficult to obtain direct economic performance returns, and the operators cannot obtain premium economic returns from the processing and development. As a result, the model has abundant public goods but insufficient marketability, and both the government and the operator are slack in development. The second difficulty is that the government may create an administrative monopoly in order to obtain a return on the asset's value added, restricting competition and preventing the public interest from being fully satisfied. This is particularly evident under the concession model.
These two difficulties are in contrast to each other, reflecting the contradictions between public interest and operation, equal access to the public and special access to public data by specific subjects, and public service function and asset value-added function in the authorised operation of public data. The key to solving this problem is twofold: firstly, to balance and accommodate the interests of different modes in the construction of the system; and secondly, to appropriately choose different modes of authorisation and operation according to different application scenarios, as discussed in this part.
3.1 Application Scenarios of Government Procurement Model
The government procurement model corresponds to the situation where the government assumes the public service function in the narrow sense, in which case the government should directly satisfy the public data usage needs of the society. The core scenario is the authorised operation of unconditionally open public data. Since these data are unconditionally open to the society, it means that even if there is room for value-addedness, the revenue generated by the value-addedness does not directly belong to the government, but to the whole society, and is enjoyed by the social developers according to the rules. Therefore, if the government adopts the approach of "authorised operation" to handle unconditionally open public data, the essence is that the government, through government procurement, entrusts the construction of operation centres and other operators to carry out certain treatment and processing of unconditionally open public data, so that they can be better used by society. This process does not necessarily require the granting of exclusive rights as in the case of franchising, but is more of a service commission, thus adopting the government procurement model.
For conditional open data, it is necessary to judge the specific scenarios and business forms of openness. Certain conditional open data only requires the user to have certain security and processing capabilities, and it is not competitive in the economic sense; the user can access it as long as it meets the general standards and is audited. In terms of administrative law theory, this is a licence, not a concession in the sense of authorisation. These conditional open class data can also be used in a government procurement model, where the government delegates the responsibility of data processing and user qualification vetting to the operator, who handles the data on its behalf.
3.2 Application Scenarios of the Concession Model
Concession is different from the general licensing mentioned above. A general licence is a general prohibition based on security and other reasons, which can be lifted as long as the relative proves that he/she meets the corresponding conditions, and in the process, it does not generate independent concession rights, not to mention exclusivity and "rights in rem". Franchise is the government due to the natural monopoly characteristics of a particular industry or the scarcity of resources, limited selection of operators, authorised a particular operator to engage in a particular business, which may produce and give the operator exclusive or even "in rem" rights. The application of franchising therefore requires special preconditions of legitimacy.
It is generally accepted that the prerequisite for franchising is the scarcity of resources or the natural monopoly character of a business. Although many scholars have suggested that data is non-competitive and non-exclusive because it can be replicated, in specific application scenarios, public data may still be scarce because of competition. The reason for this is that although data can be replicated, the review, collation, replication, and provision of meaningful data that meets security standards and application requirements is required to take up specific resources. With limited data processing capacity, access to data creates a crowding effect, leading to competitiveness and scarcity. In this case, there exists the rationality of applying the franchise model. On the one hand, through the franchise system, operators can be reasonably introduced to solve the problem of choosing between excess demand and scarce supply; on the other hand, through user fees, a price mechanism is formed to balance supply and demand. This scenario can be effectively applied to data that is set as a conditional open class because of its huge volume, the need to continuously occupy bandwidth or computing power, the need for special processing or the need for special ports.
In addition to the scarcity of resources, public data may also be subject to a franchising model because of its natural monopoly. The necessity of franchising arising from natural monopoly mainly means that the total demand in the market can be supplied by a single firm at minimal cost, while the service provider has to invest a sufficiently large upfront cost to serve the whole market before providing the service. Restrictions on access to firms can be justified by avoiding excessive competition while generating economies of scale and reducing costs. The judgement of natural monopoly is both a legal issue, an economic issue and a technical factual issue. From the practical experience of public data authorisation operation, the initial stage of public data processing and processing business, capital and technology investment is huge, there is a greater risk of development, centralised source supply can avoid duplication of construction, which does reflect a certain natural monopoly characteristics. But this kind of natural monopoly is also divided into phases and scenarios, once the development and use of public data into a relatively prosperous stage, it should be allowed to achieve the diversified development and use of public data through a more open competition mechanism. Therefore, whether the public data authorised operation can adopt the franchising method needs to be discussed specifically in conjunction with the development stage of the development and utilisation of public data.
It should be noted that the existence of natural monopoly in the stage of data resources only indicates the appropriateness of the franchising mode, and does not prove its necessity. For example, the authorised operation of the unconditionally open type of public data mentioned before, even if it has a natural monopoly due to inputs and other reasons and needs to be supplied by a centralised single subject, it may not necessarily be necessary to apply the franchise model, but may be directly applicable to the government procurement model. Therefore, if the franchise model is to be adopted, it is also necessary to take into account the trade-offs between the two different functions of the government, the government's financial capacity, the legitimacy of payment for social utilisation, the enterprise's willingness to develop, and the assumption of business risks, among other factors. Taking the legitimacy of payment as an example, even if the unconditional opening of public data constitutes a natural monopoly, it should be unconditionally supplied to the public in consideration of the basic nature of its demand, and there is no legitimacy of charging for it, so it is more appropriate to adopt the government procurement model, and the cost is borne by the finance.
The reason why the assessment of the application of the franchise model is so complicated is that it focuses more on the function of adding value to public assets, which may easily trigger the profit-seeking impulse of administrative subjects, resulting in the tendency of "privatisation of public data", thus affecting the realisation of the function of public service as a public good. The choice of franchise model must be rigorously analysed in terms of its applicability and necessity, and its narrow proportionality must be demonstrated through cost-benefit analysis. This rigour should also be reflected in the procedures. According to Article 3 of the Provisional Regulations on Major Administrative Decision-making Procedures, major administrative decision-making matters include: "formulating major public policies and measures for the development, utilisation and protection of important natural and cultural resources", and public data, as a kind of important resources, is analogous to this article, the government's development and utilisation of which should constitute a major administrative decision-making matter. The law should clarify the rules and procedures for weighing interests that should be followed in making authorisations for the operation of public data resources, and give higher-level administrative organs the power to revoke major administrative decisions that are flawed in their weighing.
3.3 Further classification of application scenarios
As mentioned earlier, the two main models can be further subdivided into a number of cross-models. The essence of these crossover patterns is the proportional trade-off between different functions, while from the perspective of application scenario selection, the essence is the combination of data in the two dimensions of security and value. Specifically, they can be further classified into four types:
（1）Low-risk, low-value data. This type of data can be directly opened, and if it needs to be entrusted to operate, it belongs to the typical government procurement mode. （2）Low-risk, high-value data. This type of data should be opened directly, and the government procurement model applies. However, under this type of data, the government is particularly vulnerable to the profit motive of data value to expand the application of licensing mode, thus crowding out the space of general openness, so it is necessary to pay extra attention to the protection of public service functions when choosing the mode. （3）High-risk, low-value data. This type of data can be chosen not to be made available to the community after assessing the risks. If it is really necessary to supply the society in a certain way, the government procurement mode or concession mode can be adopted according to the needs, but the security value should be placed at a higher level of the institutional arrangement.（4）High-risk, high-value data. It belongs to the typical application scenario of licensing mode authorised operation.
4 Key points of the system after classification construction
4.1 Goal Setting of Authorised Operation
What kind of public value should be achieved by authorised operation, and there is some difference in the focus of goal setting under different models. The government procurement model is mainly based on the narrow public service function, and its goal is to provide universal, high-quality public services with a clear goal orientation. The objectives of the franchising model need to take into account both operational and public welfare, and although it contains the operational objective of data value-added, it is still part of the broad public service, and the growth of economic interests cannot be taken as the only criterion in the design of the system, and it should also be taken into account in the consideration of the public interests such as data security, data service quality, and the interests of the data source subject and the data users.
From the perspective of controlling administrative power, it should be made clear in the target setting that if a public data should be applied to the government procurement model, it can only be based on public interest objectives but not on operational objectives; while if a public data can be used in the franchising model, it can take into account the operational objectives, but not only the operational objectives.
Although the franchising system is a recognition of natural monopoly, it is also a control of natural monopoly. In the establishment of a concession, competitiveness is introduced through bidding and other mechanisms to find the optimal operator. Optimality here includes both economic objectives and the public good objective of better and more efficient service provision. Concession tendering is not only about choosing an operator with high direct economic returns, but also about whether the operator can provide better and more convenient data services to the community. Competitive requirements are set out in the franchising system precisely to introduce competition into the monopoly industry and externalise the benefits of its monopoly. The dual objectives of franchising are reflected in the institutional arrangement, which means that the franchisor cannot be selected only through price competition, but also requires the improvement of corresponding price control, service standard control, administrative franchise contract, performance bond, franchise fee adjustment and other administrative control methods, so as to effectively regulate and constrain the franchisor and realise its public welfare objectives.
4.2 Collection of Fees
Under the government procurement model, the operator is entrusted by the government to perform the government's public service functions. Whether society needs to pay for access to data products and services hinges on whether this public service should be paid for by the Treasury or by the users. On this issue, reference can be made to the criterion of individualised attribution. Individualised attribution means that the fee debtor, by paying the fee, receives a specific payment from the State. This payment differs from the general State mandate in favour of the individual interests of the fee debtor. Individualised attribution provides a certain standard for the fee from the point of view of formal equity. If a public service belongs to a general state task, then it should be covered by taxes and no separate user fee should be imposed. On the contrary, if it does not belong to a general task but is a special task for a specific individual, then it should be borne by the user fee itself.
On the basis of the individualised attribution theory, whether a public service should be charged or not also needs to take into account the fundamentals of the demand, the source of funds, the proportionality of the price regulation, whether the natural public property is involved in the public service, the habit of using it, the object and scope of the benefit, and the voluntary expression of intention, etc., which ultimately leads to the formation of the fee payment modes such as free of charge, cost-based fee, efficiency fee, for-profit fee, and hybrid fee.
Specifically, the government procurement model involves unconditional open class data and conditional open class data in the general licence category. With the continuous development of the digital economy, this kind of data constitutes an indispensable element of production and life, and needs to be opened as much as possible, and this kind of public data supply service thus has the nature of a basic public service; on the other hand, the development and utilisation of this kind of public data is conducive to the economic development of the whole society, and has a strong positive externality. Therefore, central policy documents and local legislation have repeatedly emphasised the general obligation of the government to promote the opening up of public data. From this perspective, although the use of public data directly benefits specific users, it is also a general obligation of the government to pay, and should generally be free of charge.
However, such free access is not absolute, and in many cases there is still a justification and necessity to charge for it. Theoretically, public data can be reproduced indefinitely without competition in the sense of economics, and belongs to pure public goods, but in practice, the use of each public data may occupy a certain amount of bandwidth and other resources, resulting in a certain degree of congestion, and become a certain degree of competition of quasi-public goods. Absolute free-of-charge will lead to the externalisation of all congestion costs when congestion effects occur, creating incentives for users to overuse and ultimately exacerbating congestion and bringing about a loss of social welfare. In such cases, consideration can be given to charging appropriate user fees to adjust the balance between supply and demand through the price mechanism and reduce the congestion effect. The purpose of the fee at this point is to adjust supply and demand, not to obtain revenue, so it is not a for-profit fee, but a hybrid fee formed on the basis of cost-based fees, combined with the efficiency of the market mechanism.
To sum up, the charging situation of the use of public data under the government procurement model is shown as follows: the government pays directly to procure services from the operator, and the social subjects do not need to pay the operator again when they acquire public data. However, if users' access to public data significantly exceeds the amount of general demand, creating excessive use pressure on the entire public data open system, corresponding fees need to be charged. Such fees are mainly based on the principle of costliness, which should be calculated not only by taking into account direct costs, but also by taking into account the opportunity costs arising from congestion benefits based on the price-supply-demand mechanism, taking efficiency into account. This kind of fee model has already been applied in similar systems, typically represented by the government information disclosure system, in which the principle of applying for the disclosure of government information is free of charge, while an information processing fee may be charged when the quantity and frequency of applications for the disclosure of government information clearly exceeds a reasonable range.
In the franchise model, an important source of revenue for the operator is user fees. Through the judgement of the legitimacy of payment, the scope limitation of the franchise mode can be inversely introduced. For data classified as conditionally open because of resource scarcity, if it is price-elastic and does not fall into the category of basic needs, it can be charged efficiently or even profitably in accordance with the market mechanism.
In addition, the understanding of data scarcity and competitiveness in both the government procurement model and the franchising model still needs to be more openly understood in relation to practical scenarios. For example, in public data licensing operations, the government not only simply provides public services, but is also a primary market supplier of data production factors. The allocation of data resources by the government itself creates competitive issues. Taking the business scenario of public data service through privacy computing and other "usable and invisible" methods as an example, this scenario can unleash the huge value of some traditionally inaccessible data through data service. However, the use of this technology requires data processing, model development and specific operations for specific industries and application scenarios, and requires a large amount of resources to be invested in the early stage. Which industries should be prioritised? Which application scenarios? This creates the problem of competition and scarcity. At the same time, the development of specific industries and scenarios will absorb a large amount of public funds, but ultimately is part of the industry-specific benefits, if such a situation is free of charge, it will be the government through the universal financial subsidies to individual industries, the fairness of doubt. Therefore, the use of data for specific industries, should be charged, or even efficiency or for-profit charges, through the market mechanism, screening the most valuable industry scenarios prioritised for development. At the same time, this is also the development of the traditional public property law theory of "free use of free, special use charges" rule, charges become a special use of the means to correct the allocation of resources.
4.3 Allocation of Benefits
While the allocation of costs discusses who should bear the costs of access to public data, the allocation of benefits discusses who should enjoy the benefits arising from the value added to public data. Benefits arising from the value-added of public data include direct benefits and indirect benefits, with direct benefits being the direct benefits arising from the authorised operation of public data, and indirect benefits being the overall positive externalities arising from the authorised operation of public data, and this discussion focuses on the allocation of direct benefits.
The government procurement model aims to provide universal and balanced public services, its operating costs are borne by the public finance, and the added value of the data value generated is shared by the society, and even if charges are levied, they are only costly and do not generate direct economic benefits, so there is no issue of direct benefit distribution under the government procurement model.
In contrast, under the franchising model, a large amount of direct economic gains will be generated by the value-added processing of public data, and how to distribute these gains is a difficult issue to be dealt with in the public data authorisation and operation system. Specifically, the main bodies entitled to participate in the distribution of benefits mainly include three categories:
4.3.1 The State
The issue of public data ownership is still hotly contested, but it is usually considered to be a public resource. Although such a public resource is different from traditional natural resources, it also carries a significant public character. Therefore, when it receives an increase in value in the form of direct benefits, it is legitimate for the state, as the trustee of a public trust, to acquire the right to distribute the benefits. In addition, in the process of forming public data, the administrative subject has also invested a lot of resources in collecting, analysing, processing and dealing with public data, in this sense, the state, as a "labourer" and "contributor", also has the right to obtain the distribution of income. Justification. However, it should be noted that public data as public resources are not the private property of a particular administrative subject, but belong to the public. The right to distribute the revenue of public data should belong to the state, the administrative subject only manages the corresponding revenue distribution work, and the final actual income should be credited to the state treasury.
4.3.2 Operation subject
The legitimacy of the operating subject to get the revenue distribution lies in its input of capital, technology, human resources and other resources. In the authorised operation of public data, the operating body not only needs to carry out general processing of public data, but also needs to further process it to form data products and services and provide them to the society. Which need to invest more costs than ordinary public data opening. As a rational economic man, the premise of the operating body to invest resources is naturally to obtain a reasonable return.
The revenue distribution of the operating entity should follow the three principles of performance-based distribution, profit but not profiteering, and risk balance. Performance-based allocation means assessing the size of the operating entity's contribution to the revenue and then determining the share of the revenue. Through performance control, the operating entity can be incentivised to provide the most needed data products and services to the society. The principle of profitability without profiteering aims to balance the public interest objectives of public data authorisation while ensuring a reasonable profit for the operating entity. Risk balance, on the other hand, emphasises that the benefits should be balanced against the risks borne by the operating entity. As a new field where technological, security and operational risks are unavoidable, the benefits should be commensurate with the risks, and the distribution of benefits is a reward for taking risks. Therefore, in order to protect innovation, the distribution of benefits should be somewhat tilted in favour of the risk-takers: for the operation fields that are already relatively mature, less benefits can be distributed to the operating entities, while for the exploratory and pioneering fields, more benefits should be allocated to the operating entities.
4.3.3 Data Source Subjects
In the process of public data formation, individuals and enterprises, as the collected parties of data, also contribute to the formation of public data. From this point of view, they are also entitled to certain gains. However, due to the overall characteristics of big data, the data sources are extremely dispersed, and it is difficult to determine the contribution of a single data source subject in the value-added of public data. If the benefits are to be allocated to each of these dispersed data source subjects, the cost will be extremely high and may even be higher than the actual benefits received by each subject. Therefore, a more feasible option is for the State to act as the data trustee and manage the benefits in a unified manner. However, under certain circumstances, data source subjects may also receive benefits directly. For example, when a data subject uses public data products or services that involve data provided by the data subject, the user fee should be exempted. This exemption is also a form of revenue sharing.
4.4 Access to operators
The efficient operation of public data licensing depends to a large extent on the choice of operators. The significance of the access system for authorised operation of public data is that, by setting certain conditions and applying statutory procedures, social entities that can truly provide data services and products to the public are allowed to operate public data. At the same time, setting the access threshold for operators provides a certain guarantee for the security of raw data, thus achieving a balance between security and utilisation. In the access to operators, both the government procurement model and the franchising model emphasise the competitive factor to select the best operator, only that the franchising model highlights the market characteristics more.
In the government procurement model, the qualification of the operator should be regulated from two aspects: firstly, the physical qualification of the operator, and secondly, the formal procedure and method of selecting the operator. In terms of operational qualification requirements, firstly, it is necessary to examine whether the operating body has the ability to provide data public services, including legal status, organisational scale, staffing, internal management capacity, experience in undertaking public services and relevant social evaluation. Second, the government needs to establish an operational evaluation mechanism to distinguish between high-level and low-level operators. This is especially true for service projects that are targeted for purchase or for which it is difficult to conduct public bidding, which needs to be done through mechanisms such as third-party evaluation. As far as access procedures are concerned, article 26 of China's Government Procurement Law provides for open tendering, invited tendering, competitive negotiation, single-source procurement, request for quotations, and other procurement methods identified by the State Council's supervision and administration department of government procurement, with open tendering being the principle, and the adoption of the other methods being subject to certain statutory circumstances.
In the franchise model, the selection of the operator involves the allocation of scarce resources or access to a natural monopoly industry, and competition is relatively restricted in the subsequent operation sessions, so there is a need to fully safeguard competition in the access sessions and establish a fair and reasonable competition mechanism. The role of the market mechanism should be given full play to, and the important purpose of the franchising model is to increase the economic incentives for the development and utilisation of public data through the market approach, and to promote the valorisation of public data factor resources. In the operator access link, the government should exercise the right of public resource trustee on behalf of the state, and select the optimal operator through the market competition mechanism.
In addition, in order to achieve a balance between operational and public interest objectives under the franchise model, specific public interest objectives should be taken as important criteria for operator selection, including but not limited to: （1）Price. Price bidding itself generates allocative and productive efficiency and can generate positive externalities for society as a whole. However, when considering specific public good objectives, it is necessary to consider not only the bidding price of the concession, i.e., "monopoly price bidding" (MPB), but also the price at which the operator provides data products and services to the society, i.e., "consumer price bidding" (CPB). （2）The effect of utilisation of public data elements. Data operation as a public data supply mechanism should take the utilisation effect of public data as an important public welfare goal, promote the flow and sharing of public data, and give full play to the value of the data.（3） Fairness in the utilisation of public data. The openness and circulation of the data itself highlights the value of the fairness objective. The operator should guarantee the access to and use of public data by multiple markets and social subjects under fair and reasonable conditions in the provision of data products and services, and promote the benefits of data utilisation and the overall growth of social welfare.
4.5 Regulation of Authorised Operation
Whether authorising the operation of public data through government procurement or franchising, the government always acts as a manager and performs administrative regulatory functions. The supervision of authorised operation of public data runs through the whole life cycle of data and the whole process of authorised operation, including supervision before, during and after the matter, mainly involving data quality, data security, data utilisation, assessment and evaluation.
Previous supervision is centred on data quality and platform construction, mainly involving issues such as whether public data comply with the types, formats and standards of open data, and whether the platform complies with the requirements of unified construction and security. The core of the ex-ante supervision lies in data utilisation and security risk. Data utilisation is demand-driven, requiring the identification, aggregation and differentiation of different levels of public data demand, and the establishment of a regular data demand docking mechanism and an accurate demand communication mechanism. In terms of security risk regulation, risks should be prevented at different stages of public data provision, aggregation, operation and use. Ex-post supervision involves the establishment of assessment and evaluation mechanisms, the construction of a system of important indicators for the authorisation and operation of public data and their quantification, and timely feedback on the status of the authorised operation through assessment, so that scientific and reasonable adjustments can be made. The government can also carry out credit management for public data service providers, operation contractors, data users and other subjects to maintain a good order of public data authorisation and operation.
Under different authorised operation models, the scope of the government's regulatory functions is the same, but the focus of management is different. In the government procurement model, the government has the responsibility to provide public data to the society without bias, and it needs to regulate the management behaviour to prevent improper exercise of power. In the franchising model, the authorised operating entities make value-added use of public data for profit-making purposes, and how to prevent them from abusing their power to gain undue competitive advantages for themselves, or even exclude other entities from normal access to and use of public data, is a problem that managers need to face and solve. Value-added utilisation is also more likely to induce a certain degree of data security risk and fair competition risk, which poses a higher challenge to the government's management capability.
Enhanced oversight of the government's own operations is also needed, with the core focus on ensuring that the objectives set are accurately met, and performance governance as a key means of doing so. Especially under the concession model, the complex social and economic benefits together constitute the public value of the government's actions, which requires the application of "public value scorecard" and other public value-based performance evaluation methods to achieve a balance between public interest and operation, efficiency and fairness.
In addition, if the legitimate rights and interests of the relative are harmed in the process of authorised operation of public data, it may also give rise to the issue of assumption of responsibility. Such liability is both a relief for the relative and a kind of after-action supervision of the authorised operation of public data. There is a certain difference in the liability sharing mechanism of public data authorised operation under different models, which mainly stems from the different nature of entrustment and concession.
In the government procurement model, the administrative subject and the operator are in a delegated and entrusted relationship. Although the operator directly interfaces with the relative to provide public services, at this time the operator is only an agent of the administrative organ, and the rights and obligations of its behaviour are ultimately borne by the principal, i.e. the administrative subject. If the relative believes that his or her rights have been infringed during the public data authorisation operation activities, he or she can obtain relief through administrative litigation and other means in accordance with the law. After assuming the corresponding responsibility, the administrative subject may recover the compensation from the operator in accordance with the law or the agreement.
In the franchising model, the operator has a relatively independent subject status and has a direct legal relationship with the counterparty. If the relative believes that his rights and interests have been infringed upon, he can directly pursue legal responsibility from the operator. The administrative organ bears the overall supervision responsibility and guarantee indirect responsibility at this time, and its legal responsibility usually appears in the form of administrative omission responsibility.
5 Conclusion
The flourishing vitality of the practice of authorised operation of public data not only demonstrates its great potential, which may constitute the key to break the problem of public data supply, but also reflects the great attraction of its economic value to the practical departments, which may form a new administrative monopoly, or even the "data land finance problem" in the new era. Therefore, in the public data authorised operation system construction, need to grasp the public value goal, balance public welfare and business. In order to achieve this, we need to clarify the complexity of the practice through classification, based on different application scenarios, the application of different norms and systems, to prevent confusion in the system, either across-the-board abandonment of the operational and its economic benefits, or excessive pursuit of the operational and ignored the public interest and the public interest behind the public interest. It is only through the construction of a refined system that the combination of efficiency and fairness can be effectively realised, and public value can be reached in the end.