Accelerating the Innovative Utilization and Social Value Transformation of Public Data Resources

In the current wave of the digital age, data has become a key force driving social development and transformation, and public data is an indispensable and important component. It carries multiple missions: it not only naturally serves the public and promotes social fairness and justice, but also demonstrates enormous operational potential against the backdrop of the booming digital economy. The clear guidance of national strategy and active practices in various regions have laid the foundation and pointed the way for the development of public data. However, to achieve its innovative utilization and social value transformation, it remains necessary to pursue in-depth exploration of balanced strategies in areas such as openness, authorized operation, incentive guarantees, data space expansion, and institutional innovation.

在当今数字化的时代浪潮中，数据已成为推动社会发展与变革的关键力量，公共数据更是其中不可或缺的重要组成部分。它承载着多重使命，不仅天然服务公众、促进社会公平正义，还在数字经济蓬勃发展的背景下展现出巨大的经营潜力。国家战略的明确指引以及各地的积极实践，为公共数据的发展奠定了基础、指明了方向。然而，要实现其创新利用与社会价值转化，仍需在开放、授权运营、激励保障、数据空间拓展与制度创新等多方面深入探索平衡策略。

I. The Connotation of Public Data and Its Mission for the Era

一、公共数据的内涵与时代使命

(1) Analysis of the Essence of Data

（一）数据本质解析

The Foundation of Public Welfare Attributes. Public data originates from the operational practice of the public sphere, and its generation is closely related to public management and services. It is naturally entrusted with the mission of serving the public and promoting social fairness and justice. Taking the field of public education as an example, schools and education departments collect data on student learning situations and the allocation of educational resources, with the aim of optimizing educational decision-making and improving educational quality, thereby ensuring that every student can enjoy fair and high-quality educational resources. This process profoundly embodies the public welfare attributes of public data, and it is precisely these public welfare attributes that constitute the fundamental value of its existence.

公益属性根基。公共数据源自公共领域的运作实践，其生成与公共管理和服务密切相关。它天然肩负着服务公众、促进社会公平正义的使命。以公共教育领域为例，学校和教育部门收集学生学习情况、教育资源配置等数据，其目的是优化教育决策、提升教育质量，进而确保每个学生都能享受到公平且优质的教育资源。这一过程深刻体现了公共数据的公益属性，而这种公益属性正是其存在的根本价值所在。

Exploring Operational Potential. With the vigorous development of the digital economy, the potential commercial value of public data is gradually being discovered. Through reasonable data analysis and innovative application, public data can create new development opportunities and economic benefits for enterprises. Taking urban traffic data as an example, the analysis and utilization of data on traffic flow and travel patterns can provide decision-making support for intelligent transportation enterprises, enabling them to develop more efficient transportation solutions. At the same time, it has a positive impact on the optimization of urban transportation and economic development, demonstrating the enormous potential of public data.

经营潜力探寻。随着数字经济的蓬勃发展，公共数据的潜在商业价值逐渐被发掘。通过合理的数据分析和创新应用，公共数据能够为企业创造新的发展机遇和经济效益。以城市交通数据为例，对交通流量、出行规律等数据的分析和利用，可以为智能交通企业提供决策支持，开发更高效的交通解决方案，同时也为城市交通的优化和经济的发展带来积极影响，展示了公共数据的巨大潜力。

(2) Policy-Driven Forces

（二）政策推动力量

National Strategic Guidance. The Third Plenary Session of the 20th Central Committee of the CPC [1]1 The Third Plenary Session of the 20th Central Committee of the CPC refers to the third plenary meeting of the 20th Central Committee of the Communist Party of China, typically held around July 2023, which focuses on economic and social reform and sets the direction for the Party's work. emphasized "cultivating a nationally integrated technology and data market" and "building and operating national data infrastructure to promote data sharing." This strategic deployment has pointed the way for the development of public data, provided a solid policy foundation for the widespread application and deep mining of public data, and promoted the efficient flow and rational allocation of public data nationwide.

国家战略指引。党的二十届三中全会强调“培育全国一体化技术和数据市场”，“建设和运营国家数据基础设施，促进数据共享”，这一战略部署为公共数据的发展指明了方向，为公共数据的广泛应用和深度挖掘提供了坚实的政策基础，推动公共数据在全国范围内的高效流通和合理配置。

Progress in Local Practices. In recent years, various regions have actively responded to the call of national policies and have successively introduced related policies and measures to promote the opening of public data. For example, the city of Chongqing took the lead in formulating detailed rules for the management of public data openness, constructed an advanced public data openness platform, attracted a large number of enterprises and innovation teams to participate in data application development, achieved remarkable results in areas such as smart government affairs and urban governance, and provided replicable experience and demonstration for other regions, promoting the effective utilization and innovative development of public data at the local level.

地方实践进展。近年来，各地积极响应国家政策号召，纷纷出台相关政策和措施推动公共数据开放。如重庆城市率先制定公共数据开放管理细则，建设了先进的公共数据开放平台，吸引了大量企业和创新团队参与数据应用开发，在智慧政务、城市治理等领域取得了显著成效，为其他地区提供了可借鉴的经验和示范，促进了公共数据在地方层面的有效利用和创新发展。

II. Core Points of the Balanced Strategy and Practical Pathways

二、平衡策略的核心要点与实践路径

(1) Meticulous Planning of the Open Dimension

（一）开放维度的精细谋划

1. Mechanisms for Sound Strategy

1.机制健全策略

Precise Setting of Management Norms. The various elements of public data openness should be clearly regulated, including precisely delineating the boundaries and scope of data openness, formulating unified and strict data standards, and rationally categorizing data types. For example, for data openness in the field of public security, it should be clearly stipulated which public security surveillance data can be opened to specific institutions after processing, in what format and according to what standards it should be opened, and a strict data quality review mechanism should be established to ensure the accuracy and reliability of the data. At the same time, improve confidentiality review and security management procedures to prevent the leakage of sensitive data, ensuring the standardization and security of public data openness.

管理规范精准设定。应明确规范公共数据开放的各项要素，包括精准划定数据开放的范围边界，制定统一且严格的数据标准，以及合理划分数据类型。例如，对于公共安全领域的数据开放，要明确规定哪些治安监控数据可以在经过处理后向特定机构开放，以何种格式和规范进行开放，建立严格的数据质量审核机制，确保数据的准确性和可靠性。同时，完善保密审查和安全管理流程，防止敏感数据泄露，保障公共数据开放的规范性和安全性。

Optimization and Upgrading of Supervision and Feedback. It is crucial to build a transparent and efficient public data openness supervision and feedback system. A dedicated online supervision platform can be established to facilitate the public's timely feedback on issues and suggestions during data use. Public demands should be handled promptly to form a virtuous interactive cycle of data supply and demand, promote the balanced development of public data public welfare services, and enhance the quality and effectiveness of public data openness. For example, by setting up channels for complaints and reports, data quality issues raised by the public can be investigated and handled in a timely manner, continuously optimizing the work of data openness.

监督反馈优化升级。构建透明、高效的公共数据开放监督和反馈体系至关重要。可以建立专门的在线监督平台，方便公众随时反馈数据使用过程中的问题和建议。及时处理公众诉求，形成数据供需的良性互动循环，促进数据公益服务的均衡发展，提升公共数据开放的质量和效果。例如，通过设立投诉举报渠道，对公众反映的数据质量问题及时进行调查和处理，不断优化数据开放工作。

2. Strategies for Constructing and Applying High-Quality Data Sets

2.优质数据集的构建与应用策略

Domain Focus and Data Refinement. Advanced data processing technologies can be applied to meticulously create a batch of high-quality and broadly influential demonstration data sets in livelihood fields, such as medical health, elderly care services, and employment security. Taking the medical health field as an example, patient medical records, medical resource distribution, and other data are deeply analyzed and integrated, providing strong data support for medical research, disease prevention and control, etc., thereby promoting innovative development in the medical industry.

领域聚焦与数据精加工。可以运用先进的数据处理技术，在民生领域，如医疗健康、养老服务、就业保障等，精心打造一批高质量且具有广泛影响力的示范数据集。以医疗健康领域为例，对患者病历、医疗资源分布等数据进行深度分析和整合，为医疗科研、疾病防控等提供有力的数据支持，推动医疗行业的创新发展。

Collaborative Promotion of Innovative Partnerships. Multiple stakeholders, including universities, research institutions, and enterprises, should be encouraged to participate jointly in cooperation and innovation. Universities can leverage their strong research capabilities to provide theoretical support and technology development, while enterprises use their market acumen to transform technologies into practical products and services. For example, in the field of elderly care services, universities and enterprises collaborate to use public elderly care data to develop intelligent elderly care service platforms, providing more convenient and personalized services for the elderly, jointly promoting the development of the elderly care industry.

创新合作协同推进。鼓励高校、科研机构、企业等多方主体共同参与合作创新。高校可凭借其深厚的科研实力提供理论支撑和技术研发，企业则利用市场敏锐度将技术转化为实际产品和服务。例如，在养老服务领域，高校与企业合作，利用公共养老数据研发智能养老服务平台，为老年人提供更加便捷、个性化的服务，共同推动养老产业的发展。

(2) Exploration of Diverse Models for Authorized Operation

（二）授权运营的多元模式探索

1. Strategies for Integrating Commercial and Public Welfare

1.经营与公益融合策略

Method for Breaking the Impasse and Constructing Incentive Mechanisms. In the initial stage, high-value government data can be prioritized for pilot openness, using this as a breakthrough to open up the situation. When a virtuous cycle of effective data supply and reasonable income distribution is formed, market mechanisms can be leveraged to encourage more public institutions to participate in the market-oriented operation of data. For example, Shanghai has opened government industrial and economic data to guide enterprises in developing industrial analysis and forecasting models, which has created economic benefits for enterprises and provided scientific basis for the government's industrial planning and policy formulation, achieving an organic combination of commercial and public welfare.

破题之法与激励机制构建。初期可优先选取具有高价值的政府数据进行开放试点，以此为突破口打开局面。当数据的有效供给与合理收益分配形成良性循环后，借助市场机制激励更多公共机构参与数据的市场化运营。比如，上海通过开放政府的产业经济数据，引导企业开发产业分析预测模型，既为企业创造了经济效益，也为政府的产业规划和政策制定提供了科学依据，实现了经营与公益的有机结合。

2. Strategies for Expanding Public-Service-Oriented Operations

2.公共服务型运营拓展策略

Specialized Cultivation of Domain Entities. In key areas such as smart city construction and ecological environment protection, specialized authorized operation entities can be cultivated. These entities should possess strong technological R&D and service capabilities, enabling them to deeply mine data value and provide innovative solutions for public services. For example, cultivate an operation entity specializing in smart city water resource management, utilizing public water resource data to optimize urban water supply systems, improve water resource utilization efficiency, and provide guarantees for the sustainable development of the city.

领域主体专业培育。可在智慧城市建设、生态环境保护等重点领域，培育专业的授权运营主体。这些主体应具备强大的技术研发和服务能力，能够深入挖掘数据价值，为公共服务提供创新解决方案。例如，培育专注于智慧城市水资源管理的运营主体，利用公共水资源数据优化城市供水系统，提高水资源利用效率，为城市的可持续发展提供保障。

Practice of the Principle of "Cost-Recovery with Minimal Profit." Relevant enterprises should develop public-interest scenarios in accordance with the principle of "cost-recovery with minimal profit." In the field of ecological environment protection, enterprises authorized to operate public environmental data provide environmental monitoring and analysis services to environmental protection departments, charging only reasonable operating costs and minimal profit, ensuring the priority realization of public welfare goals while maintaining the sustainable operation of enterprises, thereby promoting the improvement of public service quality.

保本微利实践原则。相关企业应按照“保本微利”的原则开展公益性场景开发。在生态环境保护领域，企业通过授权运营公共环境数据，为环保部门提供环境监测和分析服务，仅收取合理的运营成本和微薄利润，确保公益目标的优先实现，同时维持企业的可持续运营，促进公共服务质量的提升。

(3) Comprehensive Construction of Incentive Guarantee Mechanisms

（三）激励保障机制的全面构建

1. Incentive Measures for Public Welfare Service R&D

1.公益性服务研发激励举措

Selection Activities and Competition Organization. Regularly organize selection activities for high-quality public welfare scenarios to identify projects with potential and innovativeness. Hold data application innovation competitions to stimulate enthusiasm from all sectors of society to participate in public welfare service R&D. For example, hold a "Public Data Public Welfare Innovation Challenge" to attract numerous technology companies, social organizations, and individuals to participate, giving rise to excellent public welfare application projects such as community mutual aid platforms based on public data, promoting the innovative development of public welfare services.

遴选活动与大赛组织。定期组织开展优质公益性场景遴选活动，挖掘具有潜力和创新性的公益项目。举办数据应用创新大赛，激发社会各界参与公益服务研发的热情。例如，举办“公共数据公益创新挑战赛”，吸引众多科技企业、社会组织和个人参与，催生一批如基于公共数据的社区互助平台等优秀的公益应用项目，推动公益服务的创新发展。

Award Policies and Data Archive Construction. Formulate comprehensive award policies to reward social entities and public institutions that perform prominently in R&D of public welfare scenarios. At the same time, strengthen the traceability and analysis of public data, constructing comprehensive archives of data products or services. Record in detail the source of data, processing procedures, application scenarios, and information on all parties involved, providing a scientific basis for reasonable income distribution and ensuring the continuous advancement and healthy development of public welfare service R&D. For example, provide financial rewards and policy support to teams that successfully develop public data application projects with significant social benefits.

奖补政策与数据档案建设。制定完善的奖补政策，对在公益场景研发中表现突出的社会主体和公共机构给予奖励。同时，加强公共数据的追溯和分析，构建全面的数据产品或服务档案。详细记录数据的来源、处理过程、应用场景以及涉及的各方主体信息，为合理的收益分配提供科学依据，保障公益服务研发的持续推进和健康发展。例如，对成功研发具有显著社会效益的公共数据应用项目的团队给予资金奖励和政策支持。

2. Strategies for Infrastructure and Technological Innovation Support

2.基础设施与技术创新支撑策略

Optimization of Platform Functions and Strengthening of Data Management. Increase investment in public data openness infrastructure, optimizing the functions of open data platforms. Enhance the precision of search and the intelligence of matching, making it convenient for users to quickly and accurately obtain the required data. Strengthen the hierarchical and categorized management of data and the integration of related data, improving data usability and value. For example, in a government affairs data platform, achieve organic integration and cross-correlation analysis of data from different departments and levels, providing comprehensive and accurate data support for government decision-making.

平台功能优化与数据管理强化。加大对公共数据开放基础设施的投入，优化开放数据平台的功能。提升搜索的精准度和匹配的智能化水平，方便用户快速、准确地获取所需数据。加强数据的分级分类管理和关联数据整合，提高数据的可用性和价值。例如，在政务数据平台中，实现不同部门、不同层级数据的有机整合和关联分析，为政府决策提供全面、准确的数据支持。

Innovation and Breakthroughs in Security Technology. Actively explore new security technologies, such as quantum encryption technology and blockchain data security technology, to ensure the security of public data. Innovate in security technology means to fully release the value of data while ensuring data security. For example, use quantum encryption technology to encrypt and transmit key public data, effectively preventing data theft and tampering, providing a solid security guarantee for the openness and application of public data.

安全技术创新与突破。积极探索新型安全技术，如量子加密技术、区块链数据安全技术等，保障公共数据的安全。创新安全技术手段，在确保数据安全的前提下，充分释放数据的价值。如采用量子加密技术对关键公共数据进行加密传输，有效防范数据窃取和篡改，为公共数据的开放和应用提供坚实的安全保障。

(4) Data Space Expansion and Institutional Innovation Practices

（四）数据空间拓展与制度创新实践

1. Pathways for Expanding Personal and Enterprise Data Spaces

1.个人与企业数据空间拓展路径

Participation Models and the Role of Government Certification. Support individuals and enterprises in actively participating in the management and application of their own data, with the government playing a role in authoritative certification and supervision. Individuals can independently manage and reasonably authorize the use of their own health data, consumption data, etc., while enterprises can optimize, integrate, and innovatively apply their production and operation data. Through certification mechanisms, the government ensures the legality, security, and authenticity of data, creating a favorable environment for data circulation and application.

参与模式与政府认证作用发挥。支持个人和企业积极参与自身数据的管理和应用，政府发挥权威认证和监管作用。个人可以对自己的健康数据、消费数据等进行自主管理和合理授权使用，企业对自身的生产经营数据进行优化整合和创新应用。政府通过认证机制，确保数据的合法性、安全性和真实性，为数据的流通和应用营造良好的环境。

Synergistic Strategies for System Construction. Conduct research on technologies related to existence verification chains and data spaces, constructing a synergistic system where "individuals and enterprises lead data management and application, the government certifies data quality and compliance, and government affairs platforms provide secure and reliable authorized access services." Break down data silos, achieve efficient data circulation and sharing, stimulate the innovation vitality of data, and promote the digital transformation and high-quality development of the economy and society.

体系搭建协同策略。开展存证链、数据空间相关技术研究，构建“个人与企业主导数据管理和应用、政府认证数据质量和合规性、政务平台提供安全可靠的授权访问服务”的协同体系。打破数据壁垒，实现数据的高效流通和共享，激发数据的创新活力，推动经济社会的数字化转型和高质量发展。

2. Innovative Measures for Data Public Welfare Institutions

2.数据公益制度创新举措

Integrating the Concept of Data Philanthropy. Drawing on the development model of philanthropy, incorporate data into the realm of social public welfare. Encourage enterprises and individuals to donate valuable data resources for use in public welfare research and social services. For example, enterprises donate data on user consumption habits to help public welfare organizations carry out precision poverty alleviation and social assistance projects, improving the efficiency of allocating public welfare resources and providing new ideas and methods for solving social problems.

数据慈善理念融入。借鉴慈善事业的发展模式，将数据纳入社会公益范畴。鼓励企业和个人捐赠有价值的数据资源，用于公益研究和社会服务。例如，企业捐赠用户消费习惯数据，帮助公益组织开展精准扶贫和社会救助项目，提高公益资源的配置效率，为社会问题的解决提供新的思路和方法。

Establishment of Public Welfare Funds and Implementation of Preferential Policies. Set up dedicated data public welfare funds to support the public welfare development and utilization of public data. At the same time, grant income tax preferential policies for expenditures that meet the conditions for public welfare donations, incentivizing more entities to participate in data philanthropy activities. Through policy guidance and incentives, guide data elements to play a positive role in social distribution, promoting social fairness, justice, and sustainable development.

公益基金设立与优惠政策实施。设立专门的数据公益基金，支持公共数据的公益开发和利用项目。同时，对符合公益性捐赠条件的支出给予所得税优惠政策，激励更多主体参与数据慈善活动。通过政策引导和激励，引导数据要素在社会分配中发挥积极作用，促进社会公平正义和可持续发展。

(Author's biography: He Siyuan, Researcher at the Chongqing Research Center for the Theoretical System of Socialism with Chinese Characteristics.)

（作者简介：何思远，重庆市中国特色社会主义理论体系研究中心研究员。）

Internet Editor: Huihui

网络编辑：慧慧