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Read me
10000-ft. 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 and
http://handbook.datalad.org provides a hands-on crash-course on DataLad.
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. An annotated list of
extensions is available in
the DataLad handbook.
Support
The documentation for 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 enabling NeuroDebian, via which we
provide recent releases of DataLad. Once enabled, just do:
apt-get install datalad
Gentoo-based systems
On Gentoo-based systems (i.e. all systems whose package manager can parse ebuilds as per the Package Manager Specification), we recommend enabling the ::science overlay, via which we
provide recent releases of DataLad. Once enabled, just run:
emerge datalad
Other Linux'es via conda
conda install -c conda-forge datalad
will install the most recently released version, and release candidates are
available via
conda install -c conda-forge/label/rc datalad
Other Linux'es, macOS 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 the core functionality of DataLad,
allowing for managing datasets etc. Additional installation schemes
are available, so you can request enhanced installation via
pip install datalad[SCHEME], where SCHEME could be:
tests
to also install dependencies used by DataLad's battery of unit testsfull
to install all dependencies.
More details on installation and initial configuration can be found in the
DataLad Handbook: Installation.
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).
