GEO OSE Track 1: Advancing Open Science in Space Physics: Community-Driven Solutions and Transformative Practices for Data Access, Collaboration, and Training

Understanding the restless, electrically charged layers that surround Earth's space environment is vital because disturbances in these layers can interfere with navigation satellites, power grids, and radio links. This project will transform Madrigal, a global archive of upper-atmosphere measurements, into an open gateway that anyone can explore. A new virtual assistant powered by artificial intelligence will clarify unfamiliar terms, direct visitors to relevant datasets, and propose short, browser-based exercises that run without requiring special software. Interactive maps will reveal how electron clouds move through the sky, while step-by-step programming notebooks will demonstrate how raw observations are transformed into new information about space weather. Teachers, lifelong learners, and citizen scientists will help design these resources, ensuring the platform remains open, transparent, and continually improving. By lowering technical barriers and welcoming many perspectives, the project will expand the experience of geoscience discovery beyond specialized scientists. This project focuses on enhancing the utility and accessibility of the Madrigal database, a widely used distributed data system for space physics research, through three synergistic initiatives. First, the project introduces an AI-powered virtual assistant built on a retrieval-augmented generation framework that dynamically integrates documentation, metadata, and research literature to guide users in data discovery, analysis, and interpretation. Second, the project establishes a community-driven platform to centralize computational tools and data-analysis notebooks and employs participatory processes to streamline communication between database managers and the space-physics community. Third, the project incorporates capacity-building efforts by developing decision-rich educational modules and innovative visualization resources such as Google Earth based displays. Advanced prompt engineering and large language models integrated into the database will provide real-time, context-aware assistance. Enhanced metadata standards will improve reproducibility and interoperability. Leveraging crowdsourcing and participatory methods, the project will develop a scalable, community-driven framework for creating computational tools and educational resources, with validated evaluations conducted through controlled user studies and pre- and post-assessments. Input from database administrators, researchers, and educators will enable rapid identification of challenges and co-creation of innovative solutions tailored to geoscience infrastructures. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.