Skip to main content
x

BIDS

INCFSN:
INCFSN-18-01
Endorsed on:
Re-endorsed on:
Review comments:
License:
RRID:
RRID:SCR_016124
Tags:

About

The Brain Imaging Data Structure (BIDS) is a standard prescribing a formal way to name and organize MRI data and metadata in a file system that simplifies communication and collaboration between users and enables easier data validation and software development through using consistent paths and naming for data files. BIDS is strict regarding file organization, naming, and file metadata; but in order to support wide adoption, permits substantial flexibility in the details of how other dataset metadata are described within the standard.

Links

TrainingSpace lectures
Publications
BIDS webpage

Similar standards

OpenfMRI schema, NIDM-Experiment, EEG Study Schema, XCEDE

Commentaries on endorsed standards

BIDS and the NeuroImaging Data Model (NIDM)

Supporting software

Data processing pipelines

  • BIDS Apps (a growing set of portable containerized data processing pipelines that understand BIDS datasets)

Converters

Institution specific data management/conversion tools

Quality Assessment

Other Tools

Additional URL

Usage scenario

Use BIDS for your MRI data sets, if you want: 

  • To share your data publicly. Using BIDS speeds up the curation process, and databases such as OpenNeuro.org, LORIS, COINS, XNat, SciTran and others will accept and export datasets organized according to BIDS

  • To facilitate the reuse of your data. Simply refer collaborators to the BIDS documentation for an explanation of the organization of your files and their format

  • To validate your data. Validation tools are available that enable you to check the integrity of your dataset and easily spot missing values

  • To analyze your data using data analysis software packages that understand data organized according to BIDS

Recommendations

Use BIDS in conjunction with the Neuroimaging Data Structure (NIDM) because NIDM adds additional capabilities to track provenance and disambiguate experimental details and data elements that may have substantial ambiguity to the eventual data user. Learn more: https://f1000research.com/documents/8-1373