FAIR data gaps and collaboration willingness among hemoglobinopathy research centers.

Hemoglobinopathies, including thalassemia syndromes and sickle cell disease, require interoperable and well-annotated data systems to support multi-center research and coordinated care. However, existing datasets rarely adhere to the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. We conducted a cross-sectional, web-based survey (September 2024-March 2025) among data professionals, clinicians, and researchers within the HELIOS network to evaluate data management practices, metadata use, standards adoption, and collaboration readiness. Forty-four eligible institutional responses from 22 countries were analyzed. Half of the centers reported basic metadata documentation, 20% used recognized ontologies, and none implemented common data models such as OMOP or CDISC, and only isolated mentions of HL7 FHIR were observed. Core datasets like demographics, laboratory results, and genotypes were widely available, while advanced data types such as omics and imaging were limited. Despite limited FAIR compliance, most respondents expressed willingness to participate in federated (86%) or centralized (68%) data sharing. This study provides a structured international overview of FAIR-related gaps and collaborative potential across hemoglobinopathy centers globally.