The founding partners include Carnegie Mellon University, Purdue University, Georgia Institute of Technology, Arizona State University and The George Washington University, working through the Open Forum for AI as the university coalition, plus the Astera Institute, Hugging Face as infrastructure partner and the Open Research Community Accelerator as community partner. Participants formalise their involvement through a memorandum of understanding, and organisations can enquire via protostar@orcaopen.org.

The initiative responds to a gap between publication and usability. The US federal government invests approximately $190 billion annually in research and development, and funders such as the NIH and NSF increasingly require results and underlying data to be shared. But, as the announcement itself notes, making research publicly available does not automatically make it usable: datasets and code are often scattered across incompatible systems, held in legacy formats, or released without the documentation and metadata needed for reuse, whether by human researchers or by AI systems.

The first open challenge, hosted by Carnegie Mellon University, opens on 2 November. The demand side is already visible in Hugging Face's own figures: it hosts more than 17,000 public datasets across core scientific domains such as genomics, chemistry and climate, approaching 29,000 with medicine and mathematics included, and 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.