White Paper - Envision Portal

Eye imaging datasets are essential to advancing research in eye health and beyond. From glaucoma, diabetic retinopathy, and age-related macular degeneration (AMD) to brain-related disorders such as Alzheimer’s disease and dementia, eye imaging datasets play a growing role in both clinical care and scientific research. They have particularly been critical for the development of novel AI-based diagnostic approaches. Yet, the research community faces challenges in finding and reusing eye imaging datasets that are standardized, well-documented, and ready for Artificial Intelligence (AI) development. To address this challenge, we are developing the Envision Portal, a cloud-based, open-source platform to easily share and discover FAIR (Findable, Accessible, Interoperable, and Reusable) and AI-ready eye imaging datasets derived for clinical research. This White Paper provides an overview of the motivation, design principles, and technical architecture of the Envision Portal. It describes how the platform addresses current barriers to discovering, accessing, and reusing eye imaging datasets by promoting standardized data organization, rich metadata, transparent documentation, persistent identifiers, and best practices for FAIR and AI-ready datasets. The White Paper also outlines the Envision Portal’s data standards, governance model, and roadmap.