Framework: Data: HDR: Extensible Geospatial Data Framework towards FAIR (Findable, Accessible, Interoperable, Reusable) Science

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This project provides seamless connections among platforms, data and tools, making large scientific and social geospatial datasets directly usable in scientific models and tools. Users with little or no programming experience will be able to create and build data pipelines that collect and process data at multiple scales and convert such data into usable results. Four case studies demonstrate the capability of the data framework: flood hazard prediction, plant phenotyping, water quality monitoring and sustainable development.The project creates an extensible geospatial data framework (GeoEDF) to address prevalent geospatial data challenges, support domain science needs, and contribute to a national geospatial data and software ecosystem. Specific objectives include: - development of a plug-and-play data framework (GeoEDF), - use of the framework to address domain science needs, - development of interoperability with other cyberinfrastructures, and - dissemination of GeoEDF to the broader community. Use of modular plug-and-play application programming interfaces (APIs) would enable integration of domain-specific geospatial data in a meaningful and accessible manner, leveraging an existing cyberinfrastructure capability (HUBzero) to facilitate adoption and dissemination without reinventing existing components. The project engages a substantial number of domain scientists from a variety of stakeholder communities; by incorporating the framework into HUBzero-powered sites, the team anticipates having access to more than 750,000 users. Training will be provided to the next-generation of researchers and professionals; internship programs are planned for undergraduate and underrepresented groups. The project allows users / scientists to connect a range of data sources, potentially increasing interdisciplinary work. The ultimate goal is to put easy-to-use tools and platforms into the hands of researchers and students to conduct scientific investigations using findable, accessible, interoperable, and reusable (FAIR) science principles.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.