Paper Info
Title
Cyberinfrastructure for Open Science at the Montreal Neurological Institute.
Abstract
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. To answer this demand, the Montreal Neurological Institute has announced its commitment to Open Science, harnessing the power of making both clinical and research data available to the world (Owens, 2016a,b). As such, the LORIS and CBRAIN (Das et al., 2016) 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. Implementing the vision of Open Science at the Montreal Neurological Institute will be a concerted undertaking that seeks to facilitate data sharing for the global research community. 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.
Year
DOI
Venue
2017
10.3389/fninf.2016.00053
FRONTIERS IN NEUROINFORMATICS
Keywords
Field
DocType
neuroimaging,big data,open science framework,cyberinfrastructure,neuroscience,data sharing,bids,workflow
Data science,Biobank,Open data,Data mining,World Wide Web,Computer science,Data sharing,Cyberinfrastructure,Open science,Database encryption,Workflow,Big data
Journal
Volume
Citations 
PageRank 
10
1
0.36
References 
Authors
17
34
Name
Order
Citations
PageRank
Samir Das1936.30
tristan glatard255443.66
Christine Rogers3242.02
John Saigle410.36
Santiago Paiva510.36
Leigh C. MacIntyre670.90
Mouna Safi-Harb791.22
Marc-Etienne Rousseau840.82
Jordan Stirling910.36
Najmeh Khalili-Mahani1010.36
Dave MacFarlane1170.90
Penelope Kostopoulos12162.00
Pierre Rioux13423.33
C. Madjar14473.15
Xavier Lecours-Boucher1510.70
Sandeep Vanamala1610.36
Reza Adalat17553.68
Zia Mohaddes1810.70
Vladimir Fonov1947820.32
Sylvain Milot2010.36
Ilana Leppert2110.36
D. Louis Collins223915403.90
Thomas M. Durcan2310.36
Tara Campbell2410.36
Jeremy T. Moreau2510.36
Alain Dagher26549.26
D. Louis Collins2741.17
Jason Karamchandani2810.36
Amit Bar-Or2910.36
Edward A. Fon3010.36
Rick Hoge3110.36
Sylvain Baillet3251845.76
Guy Rouleau33211.84
Alan C. Evans343045574.95