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Learn how GA4GH helps expand responsible genomic data use to benefit human health.
Neuroscience Community
The GA4GH-INCF-BRIDGE Neuroscience Community promotes global cooperation, data sharing, and collaborative neuroscience research by creating opportunities for inter-institutional scientific collaborations, sharing practices and governance models, and the adoption of standards that benefit our research and patient communities.
The Global Alliance for Genomics and Health – International Neuroinformatics Coordinating Facility – Brain Research International Data Governance Exchange (GA4GH-INCF-BRIDGE) Neuroscience Community is a forum for researchers, clinicians, data scientists, and technical experts to collaboratively define and advance real-world neuroscience use cases through the adoption of interoperable data standards. Bringing together diverse neuroscience initiatives focused on data infrastructure, governance, harmonisation, and analytical methods, the community serves as a bridge connecting scientific discovery with the technical foundations needed for responsible and scalable data sharing.
The community provides a space to explore shared challenges across neuroscience domains — from multimodal data integration and cross-disciplinary collaborations to the development and implementation of standards that support federated analysis, reproducibility, and global cooperation. Through thematic working sessions and emerging project teams, members identify gaps, establish shared goals, and develop practical resources and examples that advance the field. Previous discussions have centred on opportunities for cross-domain learning, approaches to governance in neuroscience, and strategies for enabling interoperability and analytics across international datasets.
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Identified focus areas
Data Harmonisation
Led by: Jean-Baptiste Poline
- Establish and advance shared vocabularies, metadata standards, and data models for neuroscience.
- Promote harmonisation approaches for multimodal datasets (imaging, clinical, biological, etc.)
- Develop guidance and exemplars that improve data integration and reproducibility.
Data Governance, Analytics, Federation, and Tooling
Led by: Kimberly Ray
- Inform and shape governance frameworks aligned with real-world neuroscience needs.
- Support projects that demonstrate federated analyses and interoperable infrastructure.
- Encourage adoption and implementation of technical standards and tooling across the community.
Scientific Collaboration and Education
Scientific Collaboration and Education
Led by: Mathew Abrams
- Support cross-disciplinary collaboration and shared learning across neuroscience domains.
- Identify and promote resources, training, and educational materials for data sharing and standards adoption.
- Facilitate community engagement to surface gaps, opportunities, and emerging project ideas.
Goals
- Advance global cooperation in neuroscience by connecting international initiatives and fostering cross-institutional scientific collaboration.
- Define and progress real-world neuroscience use cases that benefit from shared standards, federated analyses, and interoperable infrastructure.
- Support adoption of GA4GH, INCF, BRIDGE and other recognised standards through practical guidance, shared examples, and community-led projects.
- Promote responsible data governance by identifying common needs and creating or informing governance models suited to neuroscience.
- Improve data harmonisation and reproducibility across multimodal datasets, including imaging, clinical, biological, and wearable data.
- Build capacity through education and training, especially for organisations or individuals with limited resources, to support data sharing and standards adoption.
Activities
- Generate actionable community projects led by Theme Leaders and Theme Teams, focusing on tangible impact such as interoperable tools, metadata standards, and shared resources.
- Organise education and training opportunities such as workshops, shared curricula, and resource libraries to support standards adoption, data stewardship, and analytics capacity across diverse organisations.
- Initiate real-world interoperability demonstrations by coordinating pilot projects that showcase practical implementation of standards, federated analyses, and data-sharing frameworks in neuroscience settings.