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Theoretical Research and Practice of "Government Data Supply Chain"
Source: Big Data Department Time: 2019-11-05

The report of the Nineteenth National Congress pointed out that the supply-side structural reform should be the main line, and efforts should be made to accelerate the construction of an industrial system for the coordinated development of the real economy, technological innovation, modern finance, and human resources. Collaborative development. The organic linkage and effective response of the above four chains depend on the coordination and coordination of the “policy chain” oriented at breaking the industry and regional barriers at the supervisory level, and promoting the Internet-based and big data as the main line at the implementation level. "Data link" driven by artificial intelligence is interspersed with linkage.

At present, about 80% of China's available, exploitable, and valuable data is concentrated in the government. To promote the development of big data, we must first promote the governance and operation of government data. In this context, data management departments such as the Big Data Administration and the Big Data Development Bureau have been set up in many places across the country to coordinate big data resource management. However, in actual operation, big data management departments generally have the phenomenon of “emphasizing creation but not management, emphasizing quantity but quality, and emphasizing utilization but value-added use”. Many essential problems in the development of big data still need to be clarified and standardized, such as data rights Unclear classification, disordered data collection, extensive data governance, low openness of data sharing, and lack of data applications.

Big data management departments urgently need a complete methodology and toolset to carry out government data governance and operations. To this end, we propose a "Government Data Supply Chain" system. By building a government data supply chain, government data governance and operation will help clear data ownership, intelligent data collection, data resource assetization, and data supply. Processization, data asset service, data service value, data security operation, and value sharing federation.

政府数据供应链理念 I. Government data supply chain concept

In the process of government data governance and operation system construction, data is the most critical production factor, and building a data chain is the core content of government data governance operations. Data chain refers to the process and mechanism of data from production, collection, storage, governance, sharing, and opening to the final application in business scenarios. To integrate the data chain, we must focus on the people and widely apply emerging technologies such as cloud computing, big data, artificial intelligence, and the Internet of Things, comprehensively aggregate various types of data such as government data, social data, and Internet data, and conduct fusion innovation to activate the value of data. To empower governance change, service upgrades and economic transformation.

In the process of building a data chain, the big data management department is the core subject. Big data management departments are not data producers, but data governance, operations, and managers. Big data management departments are generally not business innovators, but data supporters of business innovation. Therefore, we believe that the most important responsibility of the big data management department is to create a sound, benign and closed value government data supply chain for the business department.

是指围绕政府数据,以大数据管理部门为主体,通过制定统一数据标准、管理统一数据质量、保障数据全生命周期安全,从对供应部门数据的采集开始,到数据的存储、治理、共享交换、挖掘计算、开放,最后把数据供应到需求部门手中进行数据应用,将数据生产方、数据采集方、数据治理方、数据运营方、数据平台方、数据开发方、数据消费方等连成一个整体的功能网链结构,以实现政府数据资源资产化、政府数据资产服务化、政府数据服务价值化。 The government data supply chain refers to the government data and the big data management department as the main body. By formulating unified data standards, managing unified data quality, and ensuring the safety of the entire life cycle of the data, it starts from the collection of data from the supply department, to the storage of data, Governance, shared exchange, mining calculation, openness, and finally supply the data to the demand department for data application, the data producer, data collector, data governance party, data operator, data platform party, data developer, data consumer And so on to form a whole functional network chain structure, in order to realize government data resource assetization, government data asset service, and government data service value.

政府数据供应链技术架构 Technical framework of government data supply chain

1 政府 数据供应链架构图 Figure 1 Government data supply chain architecture

The overall framework of the government data supply chain is composed of five functional systems and nine process links. The five major systems consist of a data production and operation system, a data quality management system, a data value evaluation system, a data security risk control system, and a data alliance collaboration system. The nine major process links include data collection, data storage, data governance, data development, internal shared exchange, data application, external shared exchange, data opening, and data transaction. The five major systems provide comprehensive process, quality, value, security, and alliance coordination support capabilities for the nine process links. Different functional guarantee systems have their own key processes.

The data production and operation system is a comprehensive methodology and toolset for data collection and fast response data supply. The data production and operation system covers all nine functional links of the data supply chain from data collection to data transactions. It is the basis for realizing the government data supply chain and provides data resources and shared exchange capabilities for subsequent data alliance collaboration. Therefore, the construction goal of the data production and operation system is to collect and exchange data from a wide range of sources, and through data governance and development, in accordance with the internal and external sharing and exchange requirements of the government, form data assets, thereby providing a comprehensive, efficient, and reliable data supply chain Data resources to provide service capabilities. The data production and operation system supports the integration of integrated data collection, integrated data governance, intelligent orchestration data cleaning, one-stop agile big data development, AI-assisted data standardization, and full-link automated data kinship through a full-stack technical support system , thereby building Global data asset system. Only by taking full control of the global data assets can the data supply capacity of the data supply chain be maximized.

A data quality management system is a methodology and toolset for assessing the quality of public data. The key aspects of the data quality management system are data collection, data governance, data development, data application, and data transaction. Carrying out data quality assessment is an important task to guarantee the data quality level of each link of the government data supply chain, and it is helpful to promote the efficient operation of the government data supply chain. The data quality management system will create a data quality evaluation index system and corresponding tool set, establish a sound institutional system and evaluation process, evaluate public data quality, evaluate and improve data quality, and improve and optimize data services. The data quality assessment mainly evaluates the data generated in the government data supply chain and the data after governance, which is conducive to improving the standardization, accuracy and real-time serviceability of data, and providing support for the realization of data quality control and quality assurance.

The data value evaluation system is a methodology and toolset for evaluating the value of public data. The key concerns of the data value evaluation system are data collection, data governance, data development, data application, data opening, and data trading. The data value evaluation system will establish a data value evaluation index system to evaluate the value of different aspects of government public data. The data value evaluation system is an important part of the government data supply chain, and it is also the driving force for data to flow within and between government departments. The system uses a multi-dimensional value evaluation method to evaluate the value of data in each link of the data supply chain, which can reflect the value-added level of data in the supply chain circulation and the final market (shared exchange) value. Without value assessment, value appreciation cannot be reflected. The purpose of data value assessment is to measure the input and output of the overall production and operation process of the data, to clarify the priority of data value, to measure the overall value level of the data supply chain, and to provide decision-making references for government data management.

The data security risk control system is a methodology and tool set to ensure the security of government data. The key concerns of the data security risk control system are data collection, data storage, internal shared exchange, external shared exchange, data opening, and data trading. The data security risk control system is a new data-centric security system that provides data security capabilities throughout the data life cycle and is the guarantee for the normal operation and governance of government data. Its technology architecture includes four levels of data security log collection and processing, data security log storage, data security risk perception, and data security log audit. The data security risk control system should have four key capabilities: data flow risk analysis and detection, behavioral risk analysis and detection, blockchain-based audit traceability, and risk control system.

The data alliance collaboration system is a methodology and toolset for data sharing alliances and data transaction alliances. The data alliance collaboration system will create cross-provincial government data sharing and cross-industry data transactions, with the focus on external sharing and exchange, data opening, and data transactions. The role of the data alliance collaboration system is to unify the organization and management of data supply and demand parties in the supply chain to achieve a sound and healthy supply chain, closed-loop, and orderly growth. At the level of government data supply chain, the data alliance collaboration system is to organize governments at all levels and government departments to form regional, cross-regional, and vertical industry government data alliances. Based on this, the data alliance collaboration system must establish quality alliances, value alliances, and security alliances, and precipitate member management mechanisms, data management systems, data standards, data quality standards, data value assessment specifications and standards, data security wind control systems, and technical solutions. Wait.

政府数据供应链实践探索 Third, the government data supply chain practice exploration

At present, with the efforts of various parties , the "government data supply chain" system has formed a complete theory, methodology and overall structure, and has been launched in Chongqing Big Data Development Bureau, Chongqing Liangjiang New District, and Lunan District and Yubei District. The pilot has achieved good initial results. In the future, I hope to build a global data supply chain, transaction chain, and alliance chain in Chongqing, and make Chongqing a national data regional model point; make Liangjiang a model of a new type of smart city in a new national zone; and build Luannan into a smart city and beautiful countryside Development model; making Yubei a national demonstration benchmark for digital China construction.

In order to standardize the management of government data resources, Chongqing has issued “two plans and one approach” successively in 2019: the “New Smart City Construction Plan” draws up the “top-level design architecture” and “construction drawings”; the “cloud long system” implementation plan is clear The promotion mechanism and responsibilities are provided; the "Interim Measures for the Management of Government Data Resources" provides legal guarantees for the promotion work, and builds a systematic top-level design based on the government data supply chain. The “City Big Data Resource Center” that Chongqing Big Data Development Bureau is planning to build uses the “2 + 4 + N + N” architecture system to aggregate, manage, share, and open data, and through the establishment of “three lists” (catalog list, (Requirement list, responsibility list) mechanism to open up the data supply side and the demand side to promote the orderly collection of data and high-quality supply; through the establishment of a basic database, a theme database, and departmental data resource pools, support the city's smart applications in various fields. Relevant person in charge of Chongqing Big Data Development Bureau said that as the open front of the “Belt and Road”, Chongqing will build a data intelligence hub for the “Digital Silk Road” through the first trial of the government data supply chain. In the future, I hope that all provinces and autonomous regions will jointly create a government data supply chain.

Liangjiang New District put forward the "one count, two rivers" open innovation concept, and built a "one brain, two palms, one center" solution, that is, building a data brain, palm office, palm office, and city operation center, and driving data circulation through applications to achieve Data collection, sharing, openness, and fusion innovation. In the process, Liangjiang New District actively responded to the call of the Chongqing Big Data Application Development Administration, not only forming a data supply mechanism for data sharing and business innovation with various departments in the New District, but also based on a "city-district-level" two-level data supply system Carry out business innovation through data sharing and common governance. Aiming at the problems of inadequate data sharing, inadequate system and mechanism, and the need to innovate the platform construction in Liangjiang New District, a series of measures have been taken from the aspects of systems, infrastructure, platforms, and applications, and a long-term plan has been formulated. Nengjiang can become a "new area for smart government service, a new area for smart governance demonstration, a new area for smart life experience, and a new area for smart economic development."

Taonan District takes the lemon industry as the starting point and develops the "Internet + regional characteristic industries" based on the urban data brain. It helps the development of Taonan lemon industry by creating a "Lemon Index", and has continued to develop government services, urban governance, and industrial economy. extend. 实施 “智慧潼南” “ 六个 建设 :一个数据大脑承载,一笔数据资产沉淀,一 批智慧 项目 推动, 一个城市 APP服务,一个高效团队运营,一个数字生态圈形成,实现潼南“城市数据大脑”在政务、城市、产业等领域更广泛的应用,打造 智慧城市与美丽乡村融合发展的样板。 In the future, Taonan will further build a "Lemon Index 2.0" through the government data supply chain system, to further integrate the lemon industry resources with more industrial resources, and gradually open up the travel, transportation, tourism, credit and other industries; vigorously implement "smart Taonan's " six one " construction , that is : a data brain carrying, a data asset precipitation, a number of smart projects to promote, a city APP service, an efficient team operation, and a digital ecosystem formed to achieve Taonan's "city The "data brain" is more widely used in government affairs, cities, industries and other fields to create a model for the integrated development of smart cities and beautiful countryside.

依托仙桃数据谷积极构建整合数据链、激活创新链、培育人才链、配置资金链、汇聚产业链的数字经济 “五链协同”发展体系。 Relying on the Xiantao Data Valley, Yubei District actively builds a digital economy "five-chain synergy" development system that integrates data chains, activates innovation chains, cultivates talent chains, allocates capital chains, and converges industrial chains . Integrate the data chain, with data aggregation as the starting point, and explore and improve the platform-based docking mechanism of government data and social data to realize the informatization of Yubei District and realize all-round data perception; activate the innovation chain and establish the Chongqing Western Big Data Frontier Application Research Institute Promote the creation of a big data collaborative innovation system for the western region; foster a talent chain. The Peking University and other universities jointly initiated the establishment of the Chongqing Xiantao Big Data and Internet of Things Vocational Training College to carry out the training of talents in the big data intelligent industry; configure the capital chain , Through the establishment of a combination of intellectual property funds, industrial venture capital funds and equity investment funds, to provide financial support for the development of the digital economy in northern Yubei; bringing together the industrial chain, focusing on technologies such as the Internet of Things, artificial intelligence and smart cars, smart terminals, etc. Industry, establish a big data industry chain, value chain and ecosystem consisting of N companies. In the future, Yubei District will further build a digital government governance system, build a digital economy development system, improve the digital social service system, and comprehensively promote the construction of "digital Yubei".

结语 Fourth, the conclusion

    

To build a sound, closed-value government data supply chain, we need to join forces with the government, enterprises, and society to form an open government data supply chain working group, explore and study the construction and evaluation mechanism of government data supply chains, and promote the government data supply chain system. The implementation and improvement of government data mining, excavating excellent cases of government data supply chain construction and summarizing experiences for promotion, urging the implementation of government data supply chain related standards and norms, promoting the construction of big data and data supply chain talents, and continuously helping the Internet powerhouse, digital China, and smart society Construction.

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About the author: National Information Center Digital China Research Institute "Government Data Supply Chain" research joint research group, this white paper research group was initiated by the National Information Center Digital China Research Institute The management committee and other units, Tsinghua University, Peking University, Beijing Normal University, Central University of Finance and Economics, Hangzhou Shumeng Workshop Technology Co., Ltd. and other companies jointly conduct research.

This article was published in the Digital China Construction Newsletter, edited and published by the Digital Information Research Institute of the National Information Center , No. 3, 2019