Designing the Future of AI-Enabled Research: Community-Driven Insights for the NAIRR Portal

The National AI Research Resource (NAIRR) Pilot is a U.S. government-led initiative designed to broaden access to the computational, data, and educational resources needed for artificial intelligence research and training. Coordinated by the National Science Foundation, in partnership with over a dozen federal agencies, the Pilot serves as a testbed to inform the design of a future full-scale NAIRR by exploring models for access, usability, and public-private collaboration. Between Fall 2024 and Spring 2025, SGX3, the Center of Excellence for Science Gateways conducted a mixed-methods study about envisioning the future NAIRR Portal involving a national survey, eight structured focus groups and a two-day design thinking workshop, collectively engaging more than 1,200 stakeholders from different backgrounds. The findings highlight enduring challenges such as fragmented access to computational resources, limited training opportunities, and steep entry barriers to adopting AI/ML tools.The participants articulated a strong shared vision for the NAIRR Portal: a user-centered platform offering personalized access, intelligent AI assistants, integrated FAIR data practices, multilingual support and embedded frameworks for responsible AI. This vision also emphasized the importance of fostering collaboration and community through accessible features.We present concrete technical and community-oriented design recommendations, including support for real-time metadata auditing, federated authentication, and modular architecture to enable adaptable, secure, and intelligent research workflows. Taken together, these insights offer a community-validated blueprint for building a scalable, equitable, and trustworthy national AI portal that can support the next generation of researchers and innovators.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-26
DOI
https://doi.org/10.5281/zenodo.17450340
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
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article

Designing the Future of AI-Enabled Research: Community-Driven Insights for the NAIRR Portal

Zenodo (CERN European Organization for Nuclear Research)
Advanced Causal Inference Techniques
article

Designing the Future of AI-Enabled Research: Community-Driven Insights for the NAIRR Portal

article en

Abstract

The National AI Research Resource (NAIRR) Pilot is a U.S. government-led initiative designed to broaden access to the computational, data, and educational resources needed for artificial intelligence research and training. Coordinated by the National Science Foundation, in partnership with over a dozen federal agencies, the Pilot serves as a testbed to inform the design of a future full-scale NAIRR by exploring models for access, usability, and public-private collaboration. Between Fall 2024 and Spring 2025, SGX3, the Center of Excellence for Science Gateways conducted a mixed-methods study about envisioning the future NAIRR Portal involving a national survey, eight structured focus groups and a two-day design thinking workshop, collectively engaging more than 1,200 stakeholders from different backgrounds. The findings highlight enduring challenges such as fragmented access to computational resources, limited training opportunities, and steep entry barriers to adopting AI/ML tools.The participants articulated a strong shared vision for the NAIRR Portal: a user-centered platform offering personalized access, intelligent AI assistants, integrated FAIR data practices, multilingual support and embedded frameworks for responsible AI. This vision also emphasized the importance of fostering collaboration and community through accessible features.We present concrete technical and community-oriented design recommendations, including support for real-time metadata auditing, federated authentication, and modular architecture to enable adaptable, secure, and intelligent research workflows. Taken together, these insights offer a community-validated blueprint for building a scalable, equitable, and trustworthy national AI portal that can support the next generation of researchers and innovators.

Zenodo (CERN European Organization for Nuclear Research)
San Diego Supercomputer Center (US), University of California San Diego (US), Nia Association (US), The University of Texas at Austin (US)
Partnerships for the goals
Openalex Percentile: Top 37%
Advanced Causal Inference Techniques
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