DataShuttle

Datashuttle is a work in progress and is currently in alpha release v0.1.0.

Datashuttle includes tools for automated generation and transfer of neuroscience project folders formatted to the NeuroBlueprint specification.

• Manage files across multiple data-collection computers by synchronising all data to with a centrally stored project.

• Simplify data transfers by selecting only a sub-set of data to move (e.g. specific subjects, sessions or datatypes)

See the DataShuttle Documentation to get started or join the Zulip chat to discuss any questions, comments or feedback.

Installation

DataShuttle is hosted on PyPI and can be installed with pip.

pip install datashuttle

Datashuttle required Rclone for data transfers. The easiest way to install Rclone is using Miniconda:

conda install -c conda-forge rclone

See the Rclone website for alternative installation methods.

NeuroBlueprint Folder Tree

DataShuttle project folders are managed according to NeuroBlueprint.

└── project_name/
    └── raw_data/
        ├── sub-001/
        │   └── ses-001/
        │       ├── ephys/
        │       └── behav/
        │       └── anat/
        └── sub-002/
            └── ses-001/
            │   ├── behav/
            │   └── imaging/
            └── ses-002/
                └── behav/
                └── anat/

└── project_name/
    └── rawdata/[test_utils.py](tests%2Ftest_utils.py)
        ├── sub-001  /
        │   └── ses-001/
        │       ├── ephys
        │       └── behav
        │       └── anat
        └── sub-002/
            ├── ses-001/
            │   ├── behav
            │   └── imaging
            └── ses-002/
                └── behav
                └── anat