Data sharing is becoming more of a requirement as technologies mature and as global research and communications diversify. As a result, researchers are looking for practical solutions, not only to enhance scientific collaborations, but also to acquire larger amounts of data, and to access specialized datasets. In many cases, the realities of data acquisition present a significant burden, therefore gaining access to public datasets allows for more robust analyses and broadly enriched data exploration. Our goal is to utilize the years of experience in multi-site collaborative research infrastructure to implement the technical requirements to achieve this level of public data sharing in a practical yet robust manner, in support of accelerating scientific discovery.

Our ongoing development of LORIS and CBRAIN platforms have been tasked with the technical challenges specific to the institutional-level implementation of open data sharing, including:

  1. Comprehensive linking of multimodal data (phenotypic, clinical, neuroimaging, biobanking, and genomics, etc.)
  2. Secure database encryption, specifically designed for institutional and multi-project data sharing, ensuring subject confidentiality (using multi-tiered identifiers).
  3. Querying capabilities with multiple levels of single study and institutional permissions, allowing public data sharing for all consented and de-identified subject data.
  4. Configurable pipelines and flags to facilitate acquisition and analysis, as well as access to High Performance Computing clusters for rapid data processing and sharing of software tools.
  5. Robust Workflows and Quality Control mechanisms ensuring transparency and consistency in best practices.
  6. Long term storage (and web access) of data, reducing loss of institutional data assets.
  7. Enhanced web-based visualization of imaging, genomic, and phenotypic data, allowing for real-time viewing and manipulation of data from anywhere in the world.
  8. Numerous modules for data filtering, summary statistics, and personalized and configurable dashboards.

We will be involved in implementing the vision of Open Science at the Montreal Neurological Institute by developing technologies that facilitate data sharing for the global research community.

Cyberinfrastructure for Open Science at the Montreal Neurological Institute (Das et al, 2017)