Standards Developer Organizations (SDOs) and the advancement of biomedical data utility: Recommendations for modifying or extending content

Abstract

Scientific progress increasingly relies on large, complex biomedical datasets; data management concerns (heterogeneity, volume, sensitivity, and a pervasive lack of standardization) present significant challenges, especially in the context of AI adoption and precision medicine. This fragmented data landscape leads to inefficiencies, hinders interoperability, and impedes the full potential of biomedical innovation. Standards Development Organizations (SDOs) are crucial in addressing these challenges by creating common languages, frameworks, and protocols for biomedical data. This document outlines the critical importance of proactive engagement by translational researchers with SDOs, detailing various modes of participation such as correction, enrichment, alignment of existing standards, and assessing the need for implementation guidance. It identifies key SDOs in the biomedical domain (e.g., HL7, GA4GH) and discusses the processes for engaging with them, including framing requests with compelling justification, ensuring alignment, demonstrating community consensus, and understanding SDO-specific procedures. The authors emphasize that successful engagement requires collaboration with SDO communities, patience, and respect for their processes. Ultimately, robust SDO engagement and continuous feedback are indispensable for fostering a more agile and robust data ecosystem, accelerating biomedical innovation, and translating research into improved health outcomes, thereby building public trust and ensuring reliable, reproducible, and equitable research.