【新华解读】公共数据“跑起来” 示范场景建设激活数据价值

Core Insights - The release of 30 new public data "running" demonstration scenarios marks the fourth batch, totaling 100 scenarios, showcasing the increasing impact of data empowerment in various sectors such as public services, industrial development, and social governance [1][2] Group 1: Achievements and Impact - The construction of public data demonstration scenarios has effectively expanded data supply, cultivated application ecosystems, and formed replicable models, demonstrating the role of public data in empowering the real economy, expanding consumer demand, and enhancing governance capabilities [2] - Notable applications have emerged in fields like healthcare, remote sensing, low-altitude economy, and smart vehicles, illustrating how data integration can drive industrial upgrades and modern governance [2] - The implementation of authorized operations as an innovative model for public data development has led to a heightened awareness of data value, expanded practical applications across over 20 regions and 10 departments, and standardized procedures for public data usage [2][3] Group 2: Challenges and Recommendations - Despite the achievements, experts highlight ongoing challenges in public data development, emphasizing the need for collaborative advancement of both open data and authorized operations [4] - Mechanistic barriers such as reluctance and insecurity in data supply units must be addressed to facilitate a more effective data market [4] - Recommendations include incorporating public data openness and authorized operations into legal responsibilities, advancing secure data circulation technologies, and ensuring mutual support between authorized operations and data infrastructure [4] Group 3: Future Prospects - Experts predict that authorized operations of public data will see significant potential in common and well-defined scenarios, with the evolution of related institutional rules clarifying the boundaries between public and commercial data [5] - This evolution is expected to facilitate a transformation of data from mere information to resource, then to asset, and ultimately to capital, contributing a "Chinese solution" to global data value realization [5]