The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services

dc.contributor.authorAvesani, Paolo
dc.contributor.authorMcPherson, Brent
dc.contributor.authorHayashi, Soichi
dc.contributor.authorCaiafa, Cesar F.
dc.contributor.authorHenschel, Robert
dc.contributor.authorGaryfallidis, Eleftherios
dc.contributor.authorKitchell, Lindsey
dc.contributor.authorBullock, Daniel
dc.contributor.authorPatterson, Andrew
dc.contributor.authorOlivetti, Emanuele
dc.contributor.authorSporns, Olaf
dc.contributor.authorSaykin, Andrew J.
dc.contributor.authorWang, Lei
dc.contributor.authorDinov, Ivo
dc.contributor.authorHancock, David
dc.contributor.authorCaron, Bradley
dc.contributor.authorQian, Yiming
dc.contributor.authorPestilli, Franco
dc.contributor.departmentRadiology and Imaging Sciences, School of Medicineen_US
dc.date.accessioned2019-08-14T15:05:15Z
dc.date.available2019-08-14T15:05:15Z
dc.date.issued2019-05-23
dc.description.abstractWe describe the Open Diffusion Data Derivatives (O3D) repository: an integrated collection of preserved brain data derivatives and processing pipelines, published together using a single digital-object-identifier. The data derivatives were generated using modern diffusion-weighted magnetic resonance imaging data (dMRI) with diverse properties of resolution and signal-to-noise ratio. In addition to the data, we publish all processing pipelines (also referred to as open cloud services). The pipelines utilize modern methods for neuroimaging data processing (diffusion-signal modelling, fiber tracking, tractography evaluation, white matter segmentation, and structural connectome construction). The O3D open services can allow cognitive and clinical neuroscientists to run the connectome mapping algorithms on new, user-uploaded, data. Open source code implementing all O3D services is also provided to allow computational and computer scientists to reuse and extend the processing methods. Publishing both data-derivatives and integrated processing pipeline promotes practices for scientific reproducibility and data upcycling by providing open access to the research assets for utilization by multiple scientific communities.en_US
dc.identifier.citationAvesani, P., McPherson, B., Hayashi, S., Caiafa, C. F., Henschel, R., Garyfallidis, E., … Pestilli, F. (2019). The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Scientific data, 6(1), 69. doi:10.1038/s41597-019-0073-yen_US
dc.identifier.urihttps://hdl.handle.net/1805/20359
dc.language.isoen_USen_US
dc.publisherSpringer Natureen_US
dc.relation.isversionof10.1038/s41597-019-0073-yen_US
dc.relation.journalScientific Dataen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.sourcePMCen_US
dc.subjectNetwork modelsen_US
dc.subjectBrain imagingen_US
dc.subjectComputational scienceen_US
dc.subjectCognitive neuroscienceen_US
dc.subjectMagnetic resonance imagingen_US
dc.titleThe open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud servicesen_US
dc.typeArticleen_US
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