A fully open downloadable database of 1200 … A fully open downloadable database of 1200 resting state fMRI (R-fMRI) datasets collected from 33 sites around the world.
The era of discovery science for human brain function was inaugurated by the collaborative launch of the Project by leading members of the functional magnetic resonance imaging (fMRI) community. Following the precedent of full unrestricted data sharing, which has become the norm in molecular genetics, the Functional Connectomes Project (FCP) entailed the aggregation and public release of over 1200 resting state fMRI (R-fMRI) datasets collected from 33 sites around the world.
Having provided the first large-scale demonstration of the feasibility and scientific value of open sharing of R-fMRI data, the next major challenge is to make the aggregation and sharing of well-phenotyped datasets a cultural norm for the imaging community. Comprehensive phenotypic information must be made available with imaging datasets to facilitate sophisticated data-mining – a process by which novel relationships between phenotypic and imaging data can be revealed. A second paradigm shift from retrospective to prospective data sharing is also necessary. That is, in contrast to the FCP release, which primarily comprised datasets that had already been published, prospective data sharing involves regularly scheduled (e.g., weekly, monthly, or quarterly) sharing of data collected at contributing sites, as the data is being collected. The notion of sharing newly acquired data, rather than waiting until those data have been published, is novel in the imaging community, but is common practice in fields such as genetics where discovery science has been successfully implemented. In order for such a shift in practice to occur, one or more imaging groups must take the lead, and set an example for the field.
# To enhance the 1000 FCP by including comprehensive phenotypic data.
# To establish a common protocol for sharing phenotypic/metadata via the 1000 FCP.
# To initiate open, prospective data-sharing for the neuroimaging community. ta-sharing for the neuroimaging community.
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