Description
Each year, a rapidly growing volume of datasets is shared across the research community. In clinical studies, many data types are collected per participant, such as surveys, vital signs, eye images, and more. There is currently no consensus on how to organize multimodal data and include related information known as metadata. Standards like BIDS (Brain Imaging Data Structure) exist but only for structuring individual modalities. To address this challenge in the AI Ready and Exploratory Atlas for Diabetes Insights (AI-READI) project, we developed the Clinical Dataset Structure (CDS). The CDS provides a simple and intuitive way to organize clinical research data and metadata in line with the FAIR Principles. It recommends organizing multimodal clinical research datasets into one folder per data type, named as per a set convention, where applicable standard structure must then be followed within each folder.
Conference Information
Bioinformatics Open Source Conference
Identifiers
Funding Information
National Institutes of Health
Bridge2AI: Salutogenesis Data Generation Project
Grant: OT2OD032644
Authors
Aydan Gasimova
California Medical Innovations Institute
ORCID: https://orcid.org/0009-0001-6902-097X
Sanjay Soundarajan
California Medical Innovations Institute
ORCID: https://orcid.org/0000-0003-2829-8032
Nayoon Gim
Department of Ophthalmology, University of Washington
Jamie Shaffer
John F. Hardesty MD Department of Ophthalmology and Visual Sciences, Washington University
ORCID: https://orcid.org/0000-0003-4045-7665
Julia Owen
John F. Hardesty MD Department of Ophthalmology and Visual Sciences, Washington University
Aaron Lee
John F. Hardesty MD Department of Ophthalmology and Visual Sciences, Washington University
ORCID: https://orcid.org/0000-0002-7452-1648
Bhavesh Patel
California Medical Innovations Institute
ORCID: https://orcid.org/0000-0002-0307-262X