FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research

Frontiers in Neuroinformatics

Neuroscience

Francis Jeanson¹  Alana Sparks²  Bianca Lasalandra²  Moyez Dharsee²  Tom Gee²  Shahab Shahnazari²  Mojib Javadi²  Fan Dong²  Emily Martens²  F. Chris MacPhee²  Anthony L. Vaccarino²  Kenneth R. Evans²  Susan G. Evans²  Fatema Khimji³  Tom Mikkelsen³  Derek Eng³  Brendan Behan³  Heena Cheema³  Kirk Nylen⁴  Stephen R. Arnott⁵  Stephen C. Strother⁵ 

[1] Datadex, Toronto, ON, Canada;Indoc Research, Toronto, ON, Canada;Ontario Brain Institute, Toronto, ON, Canada;Ontario Brain Institute, Toronto, ON, Canada;Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada;Rotman Research Institute, Toronto, ON, Canada;

关键词: neuroinformatics;    neuroscience;    data sharing;    data management;    FAIR;   

DOI  :  10.3389/fninf.2023.1158378

 received in 2023-02-03, accepted in 2023-04-10,  发布年份 2023

来源: Frontiers

【 摘 要 】

The effective sharing of health research data within the healthcare ecosystem can have tremendous impact on the advancement of disease understanding, prevention, treatment, and monitoring. By combining and reusing health research data, increasingly rich insights can be made about patients and populations that feed back into the health system resulting in more effective best practices and better patient outcomes. To achieve the promise of a learning health system, data needs to meet the FAIR principles of findability, accessibility, interoperability, and reusability. Since the inception of the Brain-CODE platform and services in 2012, the Ontario Brain Institute (OBI) has pioneered data sharing activities aligned with FAIR principles in neuroscience. Here, we describe how Brain-CODE has operationalized data sharing according to the FAIR principles. Findable—Brain-CODE offers an interactive and itemized approach for requesters to generate data cuts of interest that align with their research questions. Accessible—Brain-CODE offers multiple data access mechanisms. These mechanisms—that distinguish between metadata access, data access within a secure computing environment on Brain-CODE and data access via export will be discussed. Interoperable—Standardization happens at the data capture level and the data release stage to allow integration with similar data elements. Reusable - Brain-CODE implements several quality assurances measures and controls to maximize data value for reusability. We will highlight the successes and challenges of a FAIR-focused neuroinformatics platform that facilitates the widespread collection and sharing of neuroscience research data for learning health systems.

【 授权许可】

Unknown   
Copyright © 2023 Behan, Jeanson, Cheema, Eng, Khimji, Vaccarino, Gee, Evans, MacPhee, Dong, Shahnazari, Sparks, Martens, Lasalandra, Arnott, Strother, Javadi, Dharsee, Evans, Nylen and Mikkelsen.