Welcome to Cloud-BIDS-Layout’s documentation!

Cloud-BIDS-Layout is a lightweight wrapper for pybids’ BIDS.Layout that can grab BIDS studies from Amazon S3.

Motivation

The Brain Imaging Data Structure (BIDS) is an intuitive, accessible, and community-driven data specification for neuroimaging data. Pybids is an exceptionally written Python library that makes it easy for researchers to query, summarize, and manipulate BIDS-compliant data. However, it’s workhorse BIDSLayout class doesn’t index remote datasets stored in the cloud. That’s where Cloud-BIDS-Layout comes in.

Cloud-BIDS-Layout allows its user to specify a remote location for a BIDS-Compliant dataset. Currently only Amazon S3 locations are supported but support for Google Cloud Storage and others is coming soon. Cloud-BIDS-Layout creates a lightweight semblance of the remote dataset, just enough to pass to pybids’ BIDSLayout for indexing. The user can then use pybids’ familiar .get() method to select a subset of the study that they wish to download to the host. See Usage for more details.

Installation and usage

To install Cloud-BIDS-Layout and see usage details visit Installation and Usage.

Documentation and API

Most users will only need to interact with the CloudBIDSLayout class. See Usage for more details.

Bugs and issues

If you are having issues, please let us know by opening up a new issue. You will probably want to tag your issue with the “bug” or “question” label.

Contribute

We invite you to contribute to Cloud-BIDS-Layout. Take a look at the source code. Or tackle one of the open issues. Issues labeled “help wanted” or “good first issue” are particularly appropriate for beginners.

License

The project is licensed under the MIT license.

Acknowledgements

The development of Cloud-BIDS-Layout is supported through grant 1RF1MH121868-01 from the National Institutes for Mental Health/The BRAIN Initiative.

We are also grateful for support from the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation to the University of Washington eScience Institute Data Science Environment, as well as support from the Washington Research Foundation to eScience and to the University of Washington Institute for Neuroengineering.