Hugging Face launches Project ProtoStar to make publicly funded science AI-ready

Hugging Face announced Project ProtoStar on October 29, an initiative that brings universities, research organizations, industry and the open science community together around one goal: making publicly funded research easier to discover, reuse and build on, especially for AI-driven work.

The founding partners are specific. Carnegie Mellon University, Purdue University, Georgia Tech, Arizona State University and George Washington University join through the Open Forum for AI as the university coalition partner, alongside the Astera Institute, Hugging Face as infrastructure partner and the Open Research Community Accelerator through its Fostering Innovation Network as community partner.

Participating organizations formalize involvement through a memorandum of understanding supporting the release of suitable scientific datasets, models and code in AI-ready formats on open infrastructure. Organizations that want to join can write to protostar@orcaopen.org.

The policy backdrop is money and mandates. The U.S. federal government invests roughly $190 billion a year in research and development, and agencies including the NIH and NSF have tightened public-access requirements, asking researchers to plan for sharing underlying data. Hugging Face is one of ten generalist repositories NIH lists for research data.

Public availability is not the same as usability. Scientific datasets, models and code are often scattered across incompatible systems, stuck in static or legacy formats, or released without the documentation, metadata and provenance needed to interpret and reuse them. That makes it hard for researchers to build on prior work and harder still for AI systems to discover and combine resources across disciplines.

Demand is already visible on the platform. Hugging Face hosts more than 17,000 public datasets across core scientific domains such as genomics, protein design, chemistry, weather and climate, Earth observation and astronomy, approaching 29,000 when medicine and mathematics are included. Researchers shared more than three times as many new science datasets in the first nine months of 2026 as in the same period of 2025.

Reuse also shows up in download numbers. The 18 public repositories NIH's NCBI maintains on Hugging Face have passed 11 million downloads, and NASA IMPACT's 27 repositories have drawn about 770,000 as of October 26, while 90% of dataset downloads on the platform come from fully documented datasets. As an early institutional commitment, CMU's Open Source Programs Office is encouraging researchers to publish suitable datasets, AI models and other outputs on Hugging Face.

The first challenge is Climate Risk Intelligence, hosted by Carnegie Mellon from November 2 to 13. Teams will use historical weather records through 2018 for 210 U.S. cities to predict actual conditions from 2019 to 2026, scoring against observed weather on four urban-planning indicators including average annual temperature and total annual precipitation. Later challenges will be hosted by other participating institutions around their own open resources, building an evidence base for what makes scientific sharing genuinely reusable.