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Supplement applications due in May 2021
The National Institutes of Health (NIH) Office of Data Science Strategy recently announced four Notices of Special Interest for supplemental funding:
Apply byMay 14: Administrative Supplements for Workforce Development at the Interface of Information Sciences, Artificial Intelligence and Machine Learning (AI/ML), and Biomedical Sciences (NOT-OD-21-079)
- The purpose is to support the development and implementation of curricular or training activities at the interface of information science, AI/ML, and biomedical sciences to develop the competencies and skills needed to make biomedical data FAIR (findable, accessible, interoperable, and reusable) and AI/ML-ready.
- Frequently Asked Questions (FAQs)
Apply byMay 15: Administrative Supplements to Support Enhancement of Software Tools for Open Science (NOT-OD-21-091)
- These supplements will invest in research software tools with recognized value in a scientific community to enhance their impact by leveraging best practices in software development and advances in cloud computing.
- See the 28 awards made in 2020
- [UPDATED 5/11/21] NIH will accept proposals submitted by Monday, May 17, at 5 p.m.
Apply byMay 20: Support for existing data repositories to align with FAIR and TRUST principles and evaluate usage, utility, and impact (NOT-OD-21-089)
- The intent is to provide an opportunity for existing repositories of all sizes, and at different stages of establishment, to increase “FAIR”-ness and “
NIH_Workshop_on_Trustworthy_Data_Repositories_Report_7-8-2019%20FINAL.pdf (320 KB) ”-worthiness to improve their usage, utility, and impact throughout the data resource lifecycle. - FAQs
- The intent is to provide an opportunity for existing repositories of all sizes, and at different stages of establishment, to increase “FAIR”-ness and “
Apply byMay 26: Administrative Supplements to Support Collaborations to Improve the AI/ML-Readiness of NIH-Supported Data (NOT-OD-21-094)
- This opportunity is intended to support collaborations that bring together expertise in biomedicine, data management, and AI/ML to improve the AI/ML-readiness of data generated from NIH-funded research and shared through repositories, knowledgebases or other data sharing resources.
- FAQs