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: Comprehensive linking of multimodal data (phenotypic, clinical, neuroimaging, biobanking, and genomics, etc.)Secure database encryption, specifically designed for institutional and multi-project data sharing, ensuring subject confidentiality (using multi-tiered identifiers).Querying capabilities with multiple levels of single study and institutional permissions, allowing public data sharing for all consented and de-identified subject data.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.Robust Workflows and Quality Control mechanisms ensuring transparency and consistency in best practices.Long term storage (and web access) of data, reducing loss of institutional data assets.Enhanced web-based visualization of imaging, genomic, and phenotypic data, allowing for real-time viewing and manipulation of data from anywhere in the world.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.

Individual-patient prediction of meningioma malignancy and survival using the Surveillance, Epidemiology, and End Results database

“…Recent large-scale projects for population genotyping and brain imaging such as the UK biobank represent a significant opportunity in this regard. 35,36 Additionally, efforts to provide curation, as well as streamlined consent 37 and de-identification 38,39 of data from electronic medical records and picture archiving communication systems, are another important step in this direction. [40][41][42][43] Allowing for the wealth of patient data already being recorded for routine care to be used to advance predictive disease modeling has the potential to simplify specific aspects of clinical decision making, as well as improve diagnostic and prognostic accuracy for future patients.…”

The Quebec Parkinson Network: A Researcher-Patient Matching Platform and Multimodal Biorepository

“…In this way, the registry provides access to patients for investigators conducting research in PD. As the QPN Participant Registry continues to grow, the QPN is consolidating data collected through the questionnaire, patient medical records, and QPNfacilitated research studies, such as NeurO C-BIGR, in a centralized, open-access database (LORIS [Longitudinal Online Research and Imaging System]) [26][27][28]. All epidemiological, clinical, neuroimaging, neuropsychological, and biological data will then be made publicly accessible to promote data sharing throughout the PD research community, ultimately leading to new research projects and analyses.…”

A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps

“…For Human studies, to facilitate data storage, data sharing and data processing based on specific customized pipelines, different infrastructures have been proposed such as for instance COINS (Landis et al, 2016), LORIS+BRAIN (Das et al, 2016) or LONI (Rex et al, 2003) for…”