Category I: National Data Platform: A Federated National AI-ready Data Ecosystem for Discovery, Innovation, Education, and Workforce Development

National Data Platform (NDP) addresses the challenge of data and computing resource integration facilitating the nation's capacity to pursue scalable AI-driven discovery and innovation by establishing a federated and interoperable ecosystem that connects distributed data repositories and computing facilities across the U.S. NDP will reduce barriers of entry for data-driven science and enable researchers, educators, and learners to accelerate their research and innovation objectives. It will expand access to advanced capabilities and unlock the nation's full research potential across regions, institutions, sectors, and disciplines. NDP will also enable hands-on experiential learning, curriculum development, data challenges, and workforce training aligned with national priorities in AI and data science. By federating existing public investments and engaging private resources into an accessible AI innovation ecosystem, NDP will strengthen U.S. competitiveness and expand both research participation and workforce engagement in an increasingly AI-driven world. NDP will integrate geographically distributed data, computing, and AI resources and services into a cohesive, federated framework that supports end-to-end, AI-enabled scientific workflows. This will be delivered through interoperable, production-grade services and middleware that streamline secure access, integration, composability, and use of data, models, and workflows across edge, cloud, and high-performance computing (HPC) resources. By enabling heterogeneous and multimodal data types to seamlessly connect with AI-optimized computing capabilities, NDP will enable new classes of multimodal, data-intensive workflows that advance scientific efficiency, reproducibility, and methodological rigor. Its scalable distributed architecture will allow users to move from data ingestion and fusion to model training, simulation, and inference, within a unified environment, reducing the barriers associated with today’s fragmented cyberinfrastructure. NDP will employ a structured build–test–validate–deploy pipeline to mature project-developed and community-contributed tools into robust, reusable, and production-ready digital assets. Through co-design with domain scientists, applications across multiple disciplines will expose shared workflow patterns that NDP will generalize into extensible, reusable services for broad adoption. Collectively, these approaches will expand capacity across the U.S. to pursue scalable, AI-enabled scientific discovery and innovation and strengthen the nation’s leadership in AI. 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. NSF Award ID: 2609447 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT,01002829DB NSF RESEARCH & RELATED ACTIVIT,01003031DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Ilkay Altintas | Institution: University of California-San Diego, LA JOLLA, CA | Award Amount: $11,000,000 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2609447 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2609447.html