Open Science at the Montreal Neurological Institute - LORIS & CBRAIN
Montreal Neurological Institute, McGill Centre for Integrative Neuroscience, Canada
Data sharing is becoming more of a requirement as technologies mature, and global research and communication diversifies. 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 particular datasets. In many cases, acquisition realities present a significant burden, therefore gaining access to public datasets allows for more robust analyses and greater exploratory data mining.
To answer this demand, the Montreal Neurological Institute has announced the mission of Open Science, harnessing the power of making both clinical and research data available to the world (Owens, 2016). As such, the LORIS and CBRAIN (Das et al., 2015) platforms have been tasked with the technical challenges specific to the institutional-level implementation of public data sharing, including:
1) Comprehensive linking of multimodal data (clinical, genomics, imaging, phenotypic, demographic, etc.)
2) Secure database encryption, specifically designed for institutional and multi-project data sharing, ensuring patient and 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 subject data.
4) Configurable pipelines and flags to facilitate acquisition and analysis, as well as access to High Performance Computing clusters for immediate processing.
5) Robust Quality Control mechanisms usable as covariates in analysis.
6) Long term storage (and web access) of data, resulting in little attrition (i.e. lost data).
7) Enhanced web-based visualization of imaging, genomics, and phenotypic data, allowing for real-time viewing and manipulation of data from anywhere in the world.
8) Mobile data access capabilities with responsive viewing.
9) Numerous modules for data filtering, summary statistics, and personalized and configurable dashboards.
The goal of Open Science at the Montreal Neurological Institute will be a concerted undertaking that seeks to facilitate data sharing on a global scale. Our goal is to utilize the years of experience in multi-site collaborative research to implement the technical requirements to achieve this level of public data sharing in a practical, yet robust manner.
This work has been made possible with the support of NIH (http://nih.gov), CANARIE (http://www.canarie.ca), Compute Canada (http://www.computecanada.ca), the Irving Ludmer Family Foundation and the Ludmer Centre for Neuroinformatics and Mental Health (https://www.mcgill.ca/statisticalgenetics/ludmer-centre), the Montreal Neurological Institute (http://mnni.mcgill.ca), and the LORIS (http://loris.ca) and CBRAIN (http://mcin-cnim.ca/neuroimagingtechnologies/cbrain/)
Brian Owens, Montreal institute going ‘open’ to accelerate science, Science Magazine, January 21, 2016, DOI: 10.1126/science.aae0265
Samir Das, Tristan Glatard, Leigh C. MacIntyre, Cecile Madjar, Christine Rogers, Marc-Etienne Rousseau, Pierre Rioux, Dave MacFarlane, Zia Mohades, Rathi Gnanasekaran, Carolina Makowski, Penelope Kostopoulos, Reza Adalat, Najmeh Khalili-Mahani, Guiomar Niso, Jeremy T. Moreau, Alan C. Evans, The MNI data-sharing and processing ecosystem, NeuroImage, Volume 124, Part B, 1 January 2016, Pages 1188-1195, ISSN 1053-8119, http://dx.doi.org/10.1016/j.neuroimage.2015.08.076.
Databases as Topic,
High performance computing
Neuroinformatics 2016, Reading, United Kingdom, 3 Sep - 4 Sep, 2016.
(2016). Open Science at the Montreal Neurological Institute - LORIS & CBRAIN.
01 May 2016;
18 Jul 2016.
Mr. Samir Das, Montreal Neurological Institute, McGill Centre for Integrative Neuroscience, Montreal, QC, h3A 2t4, Canada, email@example.com