FAIR data gaps and collaboration willingness among hemoglobinopathy research centers

Hemoglobinopathies such as thalassemia syndromes and sickle cell disease represent a significant global health burden that necessitates sophisticated, interoperable data systems for effective multi-center research and coordinated clinical care. Prior research has shown that the successful management of these complex genetic conditions depends heavily on the ability of diverse institutions to share well-annotated datasets across international borders. These digital repositories must maintain high levels of structural integrity to support the rigorous demands of modern hematological investigations and therapeutic development. Scientific progress in this field remains hindered when information silos prevent the integration of patient records from different geographic regions or healthcare systems. Existing datasets rarely align with the Findable, Accessible, Interoperable, and Reusable (FAIR) principles, which serve as the gold standard for modern scientific data stewardship. This absence of evidence motivated a comprehensive assessment of the current data management landscape within specialized research networks to identify specific infrastructural deficiencies.

This investigation evaluates the current state of data management practices, metadata utilization, and standards adoption among international hemoglobinopathy research centers within the HELIOS network. Researchers sought to quantify the prevalence of recognized ontologies and common data models that facilitate the exchange of complex medical information. The study aimed to identify the specific technical and organizational barriers that prevent institutions from achieving full compliance with established Findable, Accessible, Interoperable, and Reusable (FAIR) guidelines. Assessing the willingness of clinicians and data professionals to participate in various collaborative models, such as federated or centralized sharing, constituted a primary objective of the survey. The team focused on mapping the availability of diverse data types, ranging from routine clinical demographics to advanced molecular omics and diagnostic imaging. Understanding these gaps provides a necessary foundation for designing future informatics interventions that can unify global efforts in treating inherited blood disorders.

Investigators deployed a cross-sectional, web-based survey designed to elicit detailed information regarding institutional data handling and collaboration readiness from a global cohort. The sampling frame targeted a diverse group of stakeholders, including data professionals, frontline clinicians, and academic researchers operating within the established HELIOS network. Data collection activities spanned a six-month period from September 2024 to March 2025 to ensure a contemporary and comprehensive snapshot of the field's technological status. Forty-four eligible institutional responses originating from twenty-two different countries provided the primary data for this descriptive and analytical study. The survey instrument specifically queried the use of standardized frameworks like the Observational Medical Outcomes Partnership (OMOP) and the Clinical Data Interchange Standards Consortium (CDISC). Statistical analysis focused on the frequency of metadata documentation and the sporadic implementation of the Health Level Seven Fast Healthcare Interoperability Resources (HL7 FHIR) standard.

Analysis of the institutional responses revealed that exactly half of the participating centers maintained only basic metadata documentation, which significantly limits the discoverability of their research assets. Only 20% of the surveyed organizations utilized recognized ontologies, and remarkably, none of the centers had implemented comprehensive common data models such as the Observational Medical Outcomes Partnership (OMOP) or the Clinical Data Interchange Standards Consortium (CDISC). Core datasets including patient demographics, laboratory results, and genotypes were widely available across the network, providing a solid base for potential integration. Advanced information categories such as high-resolution imaging and multi-omics data were found in only a limited number of specialized institutions. Despite low compliance with Findable, Accessible, Interoperable, and Reusable (FAIR) standards, 86% of respondents expressed willingness to join federated sharing networks. Centralized data sharing models also received substantial support, with 68% of the centers indicating their readiness to contribute to a unified global repository.

The findings highlight a substantial discrepancy between the high level of collaborative intent among researchers and the current lack of technical infrastructure required for Findable, Accessible, Interoperable, and Reusable (FAIR) data exchange. Improving the adoption of standardized ontologies and metadata frameworks is essential for transforming fragmented datasets into reusable resources that can drive international hematology research. Future strategic investments should focus on implementing common data models to overcome the interoperability hurdles identified in this global survey. The strong preference for federated sharing suggests that decentralized, privacy-preserving technologies may offer the most viable path forward for international data integration. Addressing these identified FAIR data gaps will likely enhance the quality of coordinated care and accelerate the discovery of novel treatments for sickle cell disease and thalassemia. Strengthening the digital foundations of hemoglobinopathy research centers remains a fundamental prerequisite for the success of future global health informatics initiatives.