18.11.2024
13:30-14:30 CET
David Amadi, London School of Hygiene and Tropical Medicine
Advancing FAIR Principles: Making Metadata Machine-Readable for Enhanced Population Health Data Sharing
This seminar will focus on the critical role of machine-readable metadata in making population health data Findable, Accessible, Interoperable, and Reusable (FAIR). We will explore the challenges and opportunities involved in implementing machine-readable metadata standards, highlighting the key steps toward achieving FAIR data. Additionally, we will discuss the potential benefits of these standards for public health research, including improved data sharing, collaboration, and decision-making. Practical examples and insights from recent work on metadata standardization in population health will be shared, with a particular emphasis on their application in global health contexts, including mental health data in low- and middle-income countries.