年 第 1 期） 信息无障碍动态 （2024 中国信息通信研究院 本期导读 一、 中央动态.............................................................................. 1 1. 李强主持召开国务院常务会议 研究发展银发经济增进 老年人福祉的政策举措 .............................. 1 2. 国务院办公厅印发《关于发展银发经济增进老年人福祉 的意见》 .......................................... 1 3. 国家发改委、工信部、民政部、商务部在国务院政策例 行吹风会上介绍《关于发展银发经济增进老年福祉的意见》 .................................................. 3 4. 国务院新闻办举行 2023 年工业和信息化发展情况新闻发 布会 .............................................. 5 二、 部委动态..................................... ...

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]