{"ID":2830837,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.09895","arxiv_id":"2512.09895","title":"Human-in-the-Loop and AI: Crowdsourcing Metadata Vocabulary for Materials Science","abstract":"Metadata vocabularies are essential for advancing FAIR and FARR data principles, but their development constrained by limited human resources and inconsistent standardization practices. This paper introduces MatSci-YAMZ, a platform that integrates artificial intelligence (AI) and human-in-the-loop (HILT), including crowdsourcing, to support metadata vocabulary development. The paper reports on a proof-of-concept use case evaluating the AI-HILT model in materials science, a highly interdisciplinary domain Six (6) participants affiliated with the NSF Institute for Data-Driven Dynamical Design (ID4) engaged with the MatSci-YAMZ plaform over several weeks, contributing term definitions and providing examples to prompt the AI-definitions refinement. Nineteen (19) AI-generated definitions were successfully created, with iterative feedback loops demonstrating the feasibility of AI-HILT refinement. Findings confirm the feasibility AI-HILT model highlighting 1) a successful proof of concept, 2) alignment with FAIR and open-science principles, 3) a research protocol to guide future studies, and 4) the potential for scalability across domains. Overall, MatSci-YAMZ's underlying model has the capacity to enhance semantic transparency and reduce time required for consensus building and metadata vocabulary development.","short_abstract":"Metadata vocabularies are essential for advancing FAIR and FARR data principles, but their development constrained by limited human resources and inconsistent standardization practices. This paper introduces MatSci-YAMZ, a platform that integrates artificial intelligence (AI) and human-in-the-loop (HILT), including cro...","url_abs":"https://arxiv.org/abs/2512.09895","url_pdf":"https://arxiv.org/pdf/2512.09895v1","authors":"[\"Jane Greenberg\",\"Scott McClellan\",\"Addy Ireland\",\"Robert Sammarco\",\"Colton Gerber\",\"Christopher B. Rauch\",\"Mat Kelly\",\"John Kunze\",\"Yuan An\",\"Eric Toberer\"]","published":"2025-12-10T18:22:57Z","proceeding":"cs.AI","tasks":"[\"cs.AI\",\"cs.DL\"]","methods":"[]","has_code":false}