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Title: Integrating the Brain Imaging Data Structure (BIDS) standard into C-PAC      
dateReleased:
10-20-2016
privacy:
not applicable
aggregation:
instance of dataset
dateCreated:
10-19-2016
refinement:
curated
ID:
doi:10.5524/100218
creators:
Clark, Daniel
Gorgolewski, Krzysztof J
,
availability:
available
types:
sequence
description:
Data acquired during neuroimaging experiments can be organized in many ways. This stems from differences in scanner software, various DICOM and NIFTI tools, and custom data organizing scripts within different laboratories. The Brain Imaging Data Structure (BIDS) specification provides a simple, straightforward solution to this problem by introducing an intuitive standard for neuroimaging data organization. The widespread adoption of BIDS can be facilitated through incorporating this standard into software projects used for neuroimaging analysis. These software packages will in turn benefit from the homogenous data structure and ease of specifying data acquisition parameters afforded by BIDS. The goal of this Brainhack project was to integrate BIDS into the Configurable Pipeline for the Analysis of Connectomes (C-PAC) a python software built on Nipype for the high-throughput analysis of resting state fMRI data. The updated C-PAC GUI reflects the “BIDS” and “Custom” options, with the “Custom” option allowing users to specify their data structure as in previous versions of C-PAC. In the future this option would be more elegantly displayed via a radio button with the input fields dynamically changing to reflect the type of input desired. Incorporating the BIDS subject list builder into C-PAC is a great step forward in bringing the standard to a broader audience. Throughout the integration process, other technologies were discovered that could further enable input data gathering across a wide range of file system types, including FTP, SFTP, Zip, S3, and an array of virtual filesystems. With further development, the overhead of preprocessing ones own neuroimaging data for discovery science can be minimized so scientists can focus on the results.
accessURL: https://doi.org/10.5524/100218
storedIn:
GigaScience Database
qualifier:
not compressed
format:
HTML
accessType:
landing page
primary:
true
authentication:
none
authorization:
none
abbreviation:
GigaDB
homePage: http://gigadb.org/
ID:
SCR:006565
name:
Giga Science Database

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