Enabling FAIR data stewardship in complex international multi-site studies: Data Operations for the Accelerating...

Area of Science:

• Neuroscience
• Psychiatry
• Data Science

Background:

• Publicly funded research mandates data sharing, posing challenges for sensitive health information.
• Balancing participant privacy with research community needs is crucial for complex studies.

Purpose of the Study:

• To describe the data operation ecosystem for the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ) project.
• To align data management with FAIR principles while addressing ethical and regulatory requirements.

Main Methods:

• Implementing robust data capture, dictionaries, and organizational principles.
• Utilizing automated pipelines for data flow, security, and quality control (QA/QC).
• Leveraging the NIMH Data Archive for data dissemination.

Main Results:

• A seamless data flow was designed, adhering to FAIR principles.
• Close-to-real-time QA/QC enabled immediate error correction and data quality enhancement.
• The system facilitated enhanced collaboration in multisite research.

Conclusions:

• The developed data operation ecosystem effectively manages sensitive mental health data.
• This approach advances research practices for multisite studies involving high-risk individuals.
• Real-time QA/QC is vital for maintaining data integrity and research efficiency.