Automated Standardization of Legacy Biomedical Metadata Using an Ontology-Constrained LLM Agent
Descriptive scientific metadata in public repositories are often incomplete and inconsistent with community standards and ontologies, limiting data FAIRness. Large language models (LLMs) offer a promising approach to automatically standardizing such metadata when the LLM is provided with knowledge of the relevant standards in machine-actionable form (e.g., as metadata templates from systems such as the CEDAR Workbench). Entry of metadata standards through prompt engineering offers only fixed snapshots of the relevant standards, however, and it relies on an LLM's pretrained knowledge to interpret and satisfy constraints related to the standard. We evaluate whether giving an LLM access to m...
| Authors | Josef Hardi, Martin J. O'Connor, Marcos Martinez-Romero et al. |
|---|---|
| Primary category | cs.DB |
| Published | 10 March 2026 |
| Last updated at source | 13 October 2026 |
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