NSF
Solicitation: 24-085
https://new.nsf.gov/funding/opportunities/leveraging-cyberinfrastructure-research-data
Posted Date: May 01, 2024
Concept Papers Required, Contact Appropriate Program Manager for dates.
Proposals Due: July, 03, 2024 by 5:00 pm Local Time
Dear Colleagues:
With this Dear Colleague Letter (DCL), the U.S. National Science Foundation (NSF), led by the Directorate for Computer and Information Science and Engineering (CISE) Office of Advanced Cyberinfrastructure (OAC), invites Early-Concept Grants for Exploratory Research (EAGER) and conference/workshop proposals that aim to leverage cyberinfrastructure to advance research data management (RDM) and public access to research data in alignment with the goals of OAC’s Cyberinfrastructure for Public Access and Open Science (CI PAOS) program [https://new.nsf.gov/funding/opportunities/cyberinfrastructure-public-access-open-science-ci] and the NSF Public Access Initiative (PAI) [https://new.nsf.gov/public-access]. The NSF PAI aims to make the results of NSF-supported research publicly available to the greatest extent possible. The CI PAOS program aims to catalyze new and transformative socio-technical partnerships supporting research data infrastructure ecosystems across domains through early-stage collaborative activities between cyberinfrastructure researchers, scientists, research computing experts, data management experts, research labs, university libraries, and other communities of practice.
Advancements in data management across all research disciplines are needed to achieve national public access goals, including to “make publications and their supporting data resulting from federally funded research publicly accessible without embargo on their free and public release”1 and implementing guidance to digital repositories that hold data from federally funded projects. This DCL responds to these needs while building upon previous NSF Dear Colleague Letters: Reproducibility and Replicability in Science (NSF 23-018), Open Science for Research Data (NSF 20-068), and Effective Practices for Data (NSF 19-069).