Content
Contains copies of the raw events associated to the bold func runs of each
subject but stored in a beh
folder.
Also contains in the derivatives
folder:
qc
the output of several quality controls
beh/group
averaged results at the group level
beh/figures
results at the group level
DataLad datasets and how to use them
This repository is a DataLad dataset. It provides
fine-grained data access down to the level of individual files, and allows for
tracking future updates. In order to use this repository for data retrieval,
DataLad is required. It is a free and open source
command line tool, available for all major operating systems, and builds up on
Git and git-annex to allow sharing,
synchronizing, and version controlling collections of large files. You can find
information on how to install DataLad at
handbook.datalad.org/en/latest/intro/installation.html.
Get the dataset
A DataLad dataset can be cloned
by running
datalad clone <url>
Once a dataset is cloned, it is a light-weight directory on your local machine.
At this point, it contains only small metadata and information on the identity
of the files in the dataset, but not actual content of the (sometimes large)
data files.
Retrieve dataset content
After cloning a dataset, you can retrieve file contents by running
datalad get <path/to/directory/or/file>`
This command will trigger a download of the files, directories, or subdatasets
you have specified.
DataLad datasets can contain other datasets, so called subdatasets. If you
clone the top-level dataset, subdatasets do not yet contain metadata and
information on the identity of files, but appear to be empty directories. In
order to retrieve file availability metadata in subdatasets, run
datalad get -n <path/to/subdataset>
Afterwards, you can browse the retrieved metadata to find out about subdataset
contents, and retrieve individual files with datalad get
. If you use
datalad get <path/to/subdataset>
, all contents of the subdataset will be
downloaded at once.
Stay up-to-date
DataLad datasets can be updated. The command datalad update
will fetch
updates and store them on a different branch (by default
remotes/origin/master
). Running
datalad update --merge
will pull available updates and integrate them in one go.
Find out what has been done
DataLad datasets contain their history in the git log
. By running git log
(or a tool that displays Git history) in the dataset or on specific files, you
can find out what has been done to the dataset or to individual files by whom,
and when.
More information
More information on DataLad and how to use it can be found in the DataLad
Handbook at
handbook.datalad.org. The
chapter "DataLad datasets" can help you to familiarize yourself with the concept
of a dataset.