Unlocking Dataset Value for AI-Enabled Scientific Discovery
This grant supports projects that enhance the value of existing scientific datasets for AI-driven research and discovery by improving data integration, analysis, and accessibility while ensuring security and community participation.
Funder: U.S. National Science Foundation
Due Dates: November 4, 2026 (Full proposal deadline; due by 5 p.m. local time) | First Wednesday in November, annually thereafter
Funding Amounts: $60M–$100M total; Planning grants up to $200K, Impact awards up to $2M, Flagship awards up to $5M; 25–50 awards expected; up to 3 years
Summary: Supports projects that enhance the value and usability of existing scientific datasets for AI-driven discovery, focusing on data curation, integration, and governance.
Key Information: No cost sharing required; open to a wide range of U.S. organizations including higher ed, nonprofits, businesses, and government entities.
Description
This NSF program aims to unlock the value of existing scientific datasets by supporting projects that make these datasets more usable for artificial intelligence (AI)-enabled scientific discovery. The program encourages innovative approaches for feature extraction, metadata generation, dataset integration, and the development of robust data pipelines for automated analysis. Projects should address dataset security, integrity, and governance, and are encouraged to leverage existing NSF-supported or national data infrastructure. The initiative is designed to foster interdisciplinary research and enable new scientific inquiries that extend beyond the original scope of data collection.
