datalad 0.10.1

data distribution geared toward scientific datasets

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10000ft overview

DataLad makes data management and data distribution more accessible. To do that, it stands on the shoulders of Git and Git-annex to deliver a decentralized system for data exchange. This includes automated ingestion of data from online portals and exposing it in readily usable form as Git(-annex) repositories, so-called datasets. The actual data storage and permission management, however, remains with the original data providers.

The full documentation is available at: http://docs.datalad.org

Extensions

A number of extensions are available that provide additional functionality for DataLad. Extensions are separate packages that are to be installed in addition to DataLad. In order to install DataLad customized for a particular domain, one can simply install an extension directly, and DataLad itself will be automatically installed with it. Here is a list of known extensions:

• tracking web resources and automated data distributions

• neuroimaging research data and workflows

• support for containerized computational environments

• webapp support [tech demo]

Support

The documentation of this project is found here: http://docs.datalad.org

All bugs, concerns and enhancement requests for this software can be submitted here: https://github.com/datalad/datalad/issues

If you have a problem or would like to ask a question about how to use DataLad, please submit a question to NeuroStars.org with a datalad tag. NeuroStars.org is a platform similar to StackOverflow but dedicated to neuroinformatics.

All previous DataLad questions are available here: http://neurostars.org/tags/datalad/

Installation

Debian-based systems

On Debian-based systems, we recommend to enable NeuroDebian from which we provide recent releases of DataLad. Once enabled, just do:

apt-get install datalad

Other Linux’es, OSX via pip

Before you install this package, please make sure that you install a recent version of git-annex. Afterwards, install the latest version of datalad from PyPi. It is recommended to use a dedicated virtualenv:

# create and enter a new virtual environment (optional)
virtualenv --python=python3 ~/env/datalad
. ~/env/datalad/bin/activate

# install from PyPi
pip install datalad

By default, installation via pip installs core functionality of datalad allowing for managing datasets etc. Additional installation schemes are available, so you could provide enhanced installation via pip install datalad[SCHEME] where SCHEME could be

• tests to also install dependencies used by unit-tests battery of the datalad

• full to install all dependencies.

There is also a Singularity container available. The latest release version can be obtained by running:

singularity pull shub://datalad/datalad

License

MIT/Expat

Contributing

See CONTRIBUTING.md if you are interested in internals or contributing to the project.

Acknowledgements

DataLad development is supported by a US-German collaboration in computational neuroscience (CRCNS) project “DataGit: converging catalogues, warehouses, and deployment logistics into a federated ‘data distribution’” (Halchenko/Hanke), co-funded by the US National Science Foundation (NSF 1429999) and the German Federal Ministry of Education and Research (BMBF 01GQ1411). Additional support is provided by the German federal state of Saxony-Anhalt and the European Regional Development Fund (ERDF), Project: Center for Behavioral Brain Sciences, Imaging Platform. This work is further facilitated by the ReproNim project (NIH 1P41EB019936-01A1).