Opportunity Information: Apply for DE FOA 0002306

The Department of Energy (DOE) Office of Science, through its Advanced Scientific Computing Research (ASCR) program, offered this funding opportunity to improve how research data and artificial intelligence (AI) models are shared and reused across the scientific community. The core goal is to make both datasets and AI/ML models FAIR: findable, accessible, interoperable, and reusable. By pushing the community toward FAIR practices, ASCR aims to speed up the creation of new AI applications that support the Office of Science mission areas and strengthen AI research and development more broadly.

The opportunity focuses on two main needs. First, ASCR is interested in FAIR benchmark data for AI, meaning well-documented, well-curated datasets that can be reliably used to train and evaluate AI systems. Benchmarks are especially important because they let researchers compare methods fairly, reproduce results, and understand where models succeed or fail. Second, ASCR wants FAIR frameworks that connect data and AI models, essentially approaches, standards, or infrastructure that capture and expose the relationship between training data, model development, and model use during inference. This includes the ability to understand what data produced a model, how it was processed, what task the model performs, and how the model should be applied or combined with additional data when making predictions or classifications.

In this announcement, "AI" is used broadly and includes machine learning, deep learning, neural networks, computer vision, and natural language processing. The FOA also clarifies key definitions: data are the digital artifacts used to generate AI models and/or used alongside models during inference, while an AI model is an inference method used to perform a task such as prediction, diagnosis, or classification. An AI task is the actual inference activity carried out by an intelligent system. In practical terms, the funding is aimed at improving the full lifecycle around AI in science: producing trustworthy datasets, creating models tied to clear provenance and documentation, and enabling others to discover, access, integrate, and reuse those assets without redoing foundational work.

Administratively, this was a discretionary funding opportunity issued as a cooperative agreement, indicating DOE expected substantial involvement during the project period rather than a hands-off grant structure. It fell under the Science and Technology and other Research and Development activity category (CFDA 81.049). Eligibility was broadly open to any type of applicant entity, subject to any additional eligibility details in the full announcement. The FOA was released on April 2, 2020, with an original closing date of May 15, 2020. DOE anticipated making about seven awards, with a maximum award size (ceiling) of $750,000 per project. The funding opportunity number was DE-FOA-0002306, titled "FAIR Data and Models for Artificial Intelligence and Machine Learning."

  • The Department of Energy - Office of Science, Office of Science in the science and technology and other research and development sector is offering a public funding opportunity titled "FAIR Data and Models for Artificial Intelligence and Machine Learning" and is now available to receive applicants.
  • Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 81.049.
  • This funding opportunity was created on Apr 02, 2020.
  • Applicants must submit their applications by May 15, 2020. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
  • Each selected applicant is eligible to receive up to $750,000.00 in funding.
  • The number of recipients for this funding is limited to 7 candidate(s).
  • Eligible applicants include: Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled Additional Information on Eligibility.
Apply for DE FOA 0002306

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