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

Area of Science:

• Neuroscience
• Health Informatics
• Data Science

Background:

• Effective health research data sharing is crucial for advancing disease understanding, prevention, treatment, and monitoring.
• A learning health system requires data to be Findable, Accessible, Interoperable, and Reusable (FAIR).
• The Ontario Brain Institute (OBI) has pioneered FAIR data sharing in neuroscience since 2012 through its Brain-CODE platform.

Purpose of the Study:

• To describe how the Brain-CODE platform operationalizes the FAIR data principles for neuroscience research.
• To highlight the successes and challenges of a FAIR-focused neuroinformatics platform.

Main Methods:

• Findable: Brain-CODE provides interactive tools for generating specific data subsets aligned with research questions.
• Accessible: Multiple data access mechanisms are offered, including metadata access, secure computing environment access, and data export.
• Interoperable: Standardization is implemented at data capture and release stages for seamless integration of data elements.
• Reusable: Quality assurance measures and controls are in place to maximize the value and reusability of the data.

Main Results:

• Brain-CODE successfully operationalizes FAIR principles, enhancing data sharing in neuroscience.
• The platform offers diverse mechanisms for data access and promotes data standardization.
• Quality control measures ensure data value and reusability for advanced research.

Conclusions:

• The Brain-CODE platform serves as a model for implementing FAIR data principles in neuroinformatics.
• This approach supports the development of learning health systems by facilitating widespread collection and sharing of neuroscience research data.
• Addressing challenges in FAIR data operationalization is key to maximizing the impact of health research data.