1. Data and Tools Integration in the Canadian Open Neuroscience Platform
- Author
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Jean-Baptiste Poline, Samir Das, Tristan Glatard, Cécile Madjar, Erin W. Dickie, Xavier Lecours, Thomas Beaudry, Natacha Beck, Brendan Behan, Shawn T. Brown, David Bujold, Michael Beauvais, Bryan Caron, Candice Czech, Moyez Dharsee, Mathieu Dugré, Ken Evans, Tom Gee, Giulia Ippoliti, Gregory Kiar, Bartha Maria Knoppers, Tristan Kuehn, Diana Le, Derek Lo, Mandana Mazaheri, Dave MacFarlane, Naser Muja, Emmet A. O’Brien, Liam O’Callaghan, Santiago Paiva, Patrick Park, Darcy Quesnel, Henri Rabelais, Pierre Rioux, Mélanie Legault, Jennifer Tremblay-Mercier, David Rotenberg, Jessica Stone, Ted Strauss, Ksenia Zaytseva, Joey Zhou, Simon Duchesne, Ali R. Khan, Sean Hill, and Alan C. Evans
- Subjects
Statistics and Probability ,Library and Information Sciences ,Statistics, Probability and Uncertainty ,Computer Science Applications ,Education ,Information Systems - Abstract
We present the Canadian Open Neuroscience Platform (CONP) portal to answer the research community’s need for flexible data sharing resources and provide advanced tools for search and processing infrastructure capacity. This portal differs from previous data sharing projects as it integrates datasets originating from a number of already existing platforms or databases through DataLad, a file level data integrity and access layer. The portal is also an entry point for searching and accessing a large number of standardized and containerized software and links to a computing infrastructure. It leverages community standards to help document and facilitate reuse of both datasets and tools, and already shows a growing community adoption giving access to more than 60 neuroscience datasets and over 70 tools. The CONP portal demonstrates the feasibility and offers a model of a distributed data and tool management system across 17 institutions throughout Canada.
- Published
- 2023
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