NSSDC's Practices toward FAIR Data and AI for Space Science

The age of big science is leading to the fact that many of today's important scientific problems and grand human challenges call for major breakthroughs through interdisciplinary joint research. Space science research and innovative applications are facing such a situation. Open science and artificial intelligence enable a new era in the space science research and application, offering new opportunities as well as challenges, such as the absence of data governance theories and standards, data quality and interoperability to be improved, and insufficient supply of data & intelligence-driven analysis models and tools. To make good use of large-scale space science research data and effectively support across-domain joint research, the Chinese National Space Science Data Center (NSSDC), in conjunction with several universities and research institutions, has carried out a series of practices on FAIR data implementation and AI for space science, contributing to the development of a new generation of open research infrastructure. On data governance and stewardship side, NSSDC actively promotes the FAIR principles in China's space science satellite missions and large-scale ground-based observation network projects, develops a theoretical model of scientific data governance and a set of data standards. For intelligent data application, NSSDC is exploring the development of AI-ready space science big data along with the development of intelligent analysis tools and models for automatic target identification, feature extraction, correlation and causal analysis, and event evolution prediction. In this process, we found that many of these AI-ready demands coincide with FAIR principles. How to achieve AI-ready and FAIRness are two closely related goals. In fact, both need to deal with the scale disaster and dimensional disaster of domain data, to enhance the openness of scientific resources including data, models, software and scientific workflows, to adapt to the tendency of significantly increasing machine participation in the scientific research process, and to address the complexity puzzle of frontier scientific problems. Through the fusion, integration and efficient interconnection of these scientific resources, an open scientific infrastructure that supports cross-domain and cross-platform data discovery, access, analysis and mining has been established, effectively supporting joint innovation for major scientific issues. Currently, NSSDC is also exploring connections and interactions with scientific infrastructures in other related disciplines, such as astronomy, high-energy physics and Earth system science.