Making Metadata Machine-Readable as the First Step to Providing Findable, Accessible, Interoperable, and Reusable Population Health Data: Framework Development and Implementation Study.
David AmadiSylvia Kiwuwa-MuyingoTathagata BhattacharjeeAmelia TaylorAgnes N KiraggaMichael OcholaChifundo KanjalaArofan GregoryKeith TomlinJim ToddJay Greenfieldnull nullPublished in: Online journal of public health informatics (2024)
The adoption of machine-readable metadata standards is essential for ensuring the FAIRness of population health data. By embracing these standards, organizations can enhance diverse resource visibility, accessibility, and utility, leading to a broader impact, particularly in low- and middle-income countries. Machine-readable metadata can accelerate research, improve health care decision-making, and ultimately promote better health outcomes for populations worldwide.