Digital Event Horizon
Project ProtoStar, a new initiative by Hugging Face, aims to make publicly funded scientific research more accessible, reusable, and AI-ready. The project will organize a series of open challenges to test the usability of publicly funded scientific artifacts and promote scientific reuse. The first challenge, hosted by Carnegie Mellon University, will focus on climate risk intelligence and will open on November 2, 2026. Participating organizations can explore participation or collaboration by reaching out to protostar@orcaopen.org.
Project ProtoStar aims to make publicly funded scientific research more accessible, reusable, and AI-ready. The initiative encourages systematic sharing of scientific artifacts in AI-ready formats. The project addresses the gap between publicly available research and its usability. It builds on efforts to prepare public-sector data for AI and hosts over 17,000 public datasets. The project organizes open challenges to demonstrate scientific reuse and produce concrete examples of researchers building on publicly funded scientific artifacts.
Project ProtoStar, an initiative aimed at unlocking the potential of publicly funded scientific research, is set to revolutionize the way researchers and developers access, reuse, and build upon publicly funded scientific artifacts. This ambitious project, launched by Hugging Face, brings together a coalition of universities, research organizations, industry, and the open science community to make publicly funded research more accessible, reusable, and AI-ready.
The project's founding partners, including Carnegie Mellon University, Purdue University, Georgia Institute of Technology, Arizona State University, and The George Washington University, are working through the Open Forum for AI (OFAI) as the university coalition partner, while Hugging Face serves as the infrastructure partner. The Open Research Community Accelerator (ORCA) is also partnering with its Fostering Innovation Network to support the initiative.
The U.S. federal government invests approximately $190 billion annually in research and development, and federal policy increasingly expects the results to be shared publicly. However, making research publicly available does not automatically make it usable. Scientific datasets, models, and code are often scattered across incompatible systems, stored in static or legacy formats, or released without the documentation, metadata, and provenance needed to understand and reuse them.
Project ProtoStar aims to address this gap by encouraging systematic sharing of publicly funded scientific artifacts in AI-ready formats, supported by open infrastructure and practical publishing guidance. The project builds on efforts such as the National Cancer Institute's AI Data-Readiness Challenge and Hugging Face's guide to preparing public-sector data for AI.
The demand for reusable scientific resources is already evident, with Hugging Face hosting over 17,000 public datasets across core scientific domains, including genomics, protein design, chemistry, weather and climate, Earth observation, and astronomy. Researchers shared more than three times as many new science datasets on Hugging Face in the first nine months of 2026 as in the same period of 2025, with growth remaining substantial even after excluding the largest individual uploader.
To explore this, ProtoStar will organize a series of open challenges, each hosted by a participating research institution and built around scientific resources that the institution has released openly. The challenges have two complementary goals: demonstrate scientific reuse and produce concrete examples of researchers and developers building on publicly funded scientific artifacts, including applications that combine resources across institutions or disciplines.
The first challenge, hosted by Carnegie Mellon University, will open on November 2, 2026, and invites participants to test whether AI can improve predictions of urban climate conditions using historical weather data from 210 U.S. cities. Building on research by Carnegie Mellon University, teams will use climate records through 2018 to predict actual conditions from 2019 to 2026, allowing their models to be evaluated against observed weather rather than hypothetical future scenarios.
Participants will forecast four indicators relevant to urban planning: average annual temperature, total annual precipitation, the hottest day of the year, and cooling degree days, a measure of demand for air conditioning. Their predictions will be compared against simple statistical baselines, including historical averages and linear trends, to assess whether AI approaches offer meaningful improvements in accuracy.
Beyond forecasting, participants will also propose a short climate adaptation policy idea informed by what they learned from the data. This component encourages teams to connect scientific analysis with practical public benefits, such as preparing cities for extreme heat, improving energy efficiency, or managing changing precipitation patterns.
Teams will submit a Hugging Face dataset with these outputs. Forecasting performance will be assessed through a public leaderboard measuring prediction errors against established baselines, while policy ideas will receive separate consideration. Final forecasting results will be published in early 2027, once the complete 2026 weather records are available.
The ProtoStar initiative offers opportunities to put publicly funded research to work and help us learn what is needed to make AI-ready open science more widely useful. Universities, federal research agencies, national laboratories, nonprofits, and other research organizations interested in making their scientific resources more accessible and reusable are welcome to explore participation or collaboration by reaching out to protostar@orcaopen.org.
The project's hope is that ProtoStar will make it easier for publicly funded scientific work to reach the people and tools that can build on it, while generating practical evidence about the infrastructure and practices needed to support open science at scale.
Related Information:
https://www.digitaleventhorizon.com/articles/Unlocking-the-Potential-of-Publicly-Funded-Scientific-Research-The-Launch-of-Project-ProtoStar-deh.shtml
https://huggingface.co/blog/announcing-project-protostar
Published: Thu Oct 29 12:07:02 2026 by llama3.2 3B Q4_K_M
