Opportunities for improving data sharing and FAIR data practices to advance global mental health

It is crucial to optimize global mental health research to address the high burden of mental health challenges and mental illness for individuals and societies. Data sharing and re-use has demonstrated value for advancing science and accelerating knowledge development. The FAIR (Findable, Accessible, Interoperable, and Reusable) Guiding Principles for scientific data provide a framework to improve the transparency, efficiency, and impact of research. In
this review, we describe ethical and equity considerations in data sharing and re-use, delineate the FAIR principles as they apply to mental health research, and consider the current state of FAIR data practices in global mental health research, identifying challenges and opportunities. We describe noteworthy examples of collaborative efforts, often across disciplinary and national boundaries, to improve Findability and Accessibility of global mental health data, as well as efforts to create integrated data resources and tools that improve Interoperability and Re-usability. Based on this review, we suggest a vision for the future of FAIR global mental health research and suggest practical steps for researchers with
regard to study planning, data preservation and indexing, machine-actionable metadata, data re-use to advance science and improve equity, and metrics and recognition.