Policy and Framework - The State Council's "Guiding Opinions on Strengthening Digital Government Construction" emphasizes the need for integrated digital government construction, focusing on technology, business, and data integration[3] - The "14th Five-Year Plan" outlines key tasks for digital government construction, including public data sharing, co-construction of government information systems, and improving digital government service efficiency[19] - The "National Integrated Government Big Data System Construction Guide" provides a detailed blueprint for digital government construction, emphasizing unified management and data sharing[19] Service Integration - The "One Thing Done Efficiently" initiative has become a key driver for optimizing government services, with many regions establishing online service zones for streamlined processes[12] - By 2023, all provinces and cities above the prefecture level had established urban operation management platforms, enhancing grid-based management and intelligent services[12] - Over 80% of regions in China use WeChat or Alipay mini-programs to provide government services, with 31 provinces and Xinjiang Production and Construction兵团 having completed integration with the national government service platform[22] Data and Technology - The national integrated government big data platform has connected 52 departments and 32 regions, with over 2.06 million resources and 48.47 million service calls by the end of 2023[58] - Public data open platforms have seen a 32-fold increase in downloadable datasets, from 1.5 billion in 2019 to over 48 billion in 2023[27] - Large models integrating big data, IoT, AI, and digital twin technologies are expected to enhance government management and service efficiency, enabling proactive and intelligent decision-making[31] Infrastructure and Security - By 2023, over 70% of prefecture-level cities had established government cloud platforms, with the national e-government extranet covering 96.1% of townships[32] - A comprehensive security system is being developed to address terminal, network, cloud, data, and application security, ensuring the stable operation of digital government platforms[34] - The "Three Major Shifts" in digital government construction include transitioning from fragmented to unified mechanisms, from segmented to integrated services, and from passive to proactive technological responses[16]

Group 1: Public Data Importance - Public data is a crucial component of China's data supply system, characterized by its public nature, authority, and scale, holding significant value[4] - The development and utilization of public data are essential for promoting the digital economy and enhancing public governance and common prosperity[4] - Public data can improve administrative efficiency, enhance public services, and support scientific decision-making and social governance capabilities[47] Group 2: Current Challenges - There are common difficulties in public data utilization, including insufficient operational standards, lack of coordination between local and industry levels, and challenges in data quality and accessibility[2][30] - The existing public data open platforms are unevenly distributed across regions, with some areas lacking adequate platforms, leading to a fragmented data sharing environment[30] - The quality of open data is often inadequate, with issues such as low data volume and infrequent updates, affecting the timeliness and usability of the data[30] Group 3: Policy and Regulatory Framework - The "Data Twenty Articles" policy emphasizes the need for a classification and grading system for public data, promoting its authorized use and market circulation[24][64] - Numerous local governments have established regulations and management measures for public data, with over 40 provinces and cities creating or restructuring local data groups to facilitate public data operations[96] - The establishment of a clear legal framework for public data authorization and operation is underway, with various regions implementing specific guidelines and operational procedures[40][72] Group 4: Operational Models - Three main operational models for public data authorization have emerged: centralized 1-to-1, industry-specific 1-to-N, and decentralized 1-to-N models, each with its advantages and challenges[75] - The centralized 1-to-1 model is the most commonly applied, maximizing the integration value of data while simplifying authorization processes[75] Group 5: Future Prospects - The ongoing exploration of public data authorization operations is expected to enhance the market vitality and innovation in the data factor market, providing a breakthrough for its development[58][67] - The integration of social forces into public data operations through authorized models is anticipated to improve data quality and application efficiency, driving further value release[56][58]