On October 15, 2018, , a vital component of Canada鈥檚 digital infrastructure supporting research, education and innovation, announced the funding of 20 successful recipients of its Research Software funding call.
The purpose of the funding is to enable research teams in applied sciences and the humanities to adapt their existing research platforms for re-use by new research teams, including those working in different disciplines. Research platforms are complete software applications that support most of a research project鈥檚 workflow (i.e. data collection, processing, visualization, and storage).
CANARIE鈥檚 experience in funding research software has highlighted the fact that research workflow is usually similar across most projects and disciplines. As such, the goal is to allow new research teams in Canada to re-use previously funded and developed software to accelerate discovery.
The following 平特五不中 research projects have been funded to evolve their platforms鈥� capabilities to support new teams of researchers:
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鈥� Led by Dr. Alan Evans, 平特五不中
A web-based, collaborative neuroimaging research platform providing transparent access to computing and data resources available across Canada and around the world.
Software Evolution: Three new workflows will be integrated into the CBRAIN platform to support different types of electro/magneto-cephalographic (EEG/MEG) neurologic research.
Funding Amount: $225,000
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鈥� Led by Dr.Isabel Fortier, Research Institute of the 平特五不中 Health Center
A platform designed and developed to meet the data management and dissemination requirements of large observational cohort studies, which can recruit up to thousands of participants and collect large numbers data elements throughout participants鈥� lifetimes.
Software Evolution: OBiBa will be enhanced and extended to support the particular needs of clinical research infrastructures, which are different from cohort studies. These infrastructures often comprise a smaller number of participants with specific, unique challenges related to patients and their data.
Funding Amount: $225,000