Significance, challenges, and policy recommendations for strengthening database development to support AI for Science in China

With the rapid emergence of research intelligence driven by big data and artificial intelligence (AI), high-quality, openly shared scientific databases have become a strategic focal point for scientific innovation and enhancing technological competitiveness. Major countries around the world are increasingly recognizing the foundational role of scientific databases in advancing basic research. While continuously strengthening their own scientific data infrastructure through a series of initiatives, they have simultaneously imposed restrictions and suppression on the development of AI technologies in China, including those involving research data. Against this backdrop, building an autonomous and controllable scientific data ecosystem to support research intelligence is of great significance for unlocking the potential of China’s scientific data, ensuring national research security, and achieving a leap in independent innovation capacity. This study reviews international experiences in constructing databases that support research intelligence, analyzes the current status and challenges of scientific database development in China—including mismatches between the quantity and quality of data storage, insufficient openness and sharing of databases, inadequate coordination within the policy support system, and an underdeveloped database application ecosystem. Based on these findings, the study proposes strategies for strengthening China’s scientific data ecosystem, including enhancing top-level design and government support, promoting open-source and standardized management, fostering diverse collaborations, and facilitating integration with industrial applications.