CMEO: a metadata-centric ontology for clinical studies exploration and harmonization assessment

The integration of clinical research data across various institutions faces hurdles due to differing definitions, inconsistent terminologies, and inadequate support for interoperable metadata. While biomedical ontologies offer valuable tools for structuring clinical data, they have not yet been fully utilized for creating comprehensive metadata descriptors, such as variable semantics, statistical summaries, and governance elements essential for data discovery and alignment. We present the Clinical Metadata Exploration Ontology (CMEO) that builds upon well-established ontologies to provide a cohesive representation of study designs, data elements, exploratory statistics, and data reuse permissions. CMEO facilitates semantic querying for study exploration and comparison of data elements across studies, particularly when individual-level data cannot be shared. We demonstrate its utility using metadata from five studies: four heart-failure studies and one wearable-based type 1 diabetes study. After serializing, we executed SPARQL queries that operationalized study-level discovery, variable alignment across studies, and governance-constrained reuse. This FAIR-compliant, metadata-driven integration across heterogeneous sources enables scalable, privacy-conscious research and underpins federated clinical data exploration.