FAIR Data and Models for Artificial Intelligence and Machine Learning

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in making research data and artificial intelligence (AI) models findable, accessible, interoperable, and reusable (FAIR1) to facilitate the development of new AI applications in SC’s congressionally

authorized mission space, which includes the advancement of AI research and development.

In particular, ASCR is interested in supporting FAIR benchmark data for AI; and FAIR frameworks for relating data and AI models.

For this FOA, AI is inclusive of, for example, machine learning (ML), deep learning (DL), neural networks (NN), computer vision, and natural language processing (NLP).

Data, in this context, are the digital artifacts used to generate AI models and/or employed in combination with AI models during inference.

An AI model is an inference method that can be used to perform a “task,” such as prediction, diagnosis, or classification.

The model is developed using training data or other knowledge.

An AI task is the inference activity performed by an artificially intelligent system.
Related Programs

Office of Science Financial Assistance Program

Department of Energy


Office: Office of Science

Estimated Funding: $8,500,000

Who's Eligible

Relevant Nonprofit Program Categories

Obtain Full Opportunity Text:
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Additional Information of Eligibility:
All types of applicants are eligible to apply, except Federally Funded Research and Development Center (FFRDC)4 Contractors, and nonprofit organizations described in section 501(c)(4) of the Internal Revenue Code of 1986 that engaged in lobbying activities after December 31, 1995.

Other Federal agencies are not eligible to receive financial assistance awards and are therefore ineligible to submit applications.

Applicants that are not domestic organizations should be advised that: • Individual applicants are unlikely to possess the skills, abilities, and resources to successfully accomplish the objectives of this FOA.

Individual applicants are encouraged to address this concern in their applications and to demonstrate how they will accomplish the objectives of this FOA.

• Non-domestic applicants are advised that successful applications from non-domestic applicants include a detailed demonstration of how the applicant possesses skills, resources, and abilities that do not exist among potential domestic applicants.

Applications from for-profit organizations that propose research related to current commercial activity may be declined without merit review.

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Edited by: Michael Saunders

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