About this dataset

General information

This is a DataLad dataset (id: d43e3f99-c4b5-4855-a7ed-22d9c20fd099).

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.

More information on how to install DataLad and how to install it can be found in the DataLad Handbook.

Get the dataset

A DataLad dataset can be cloned by running

datalad clone https://github.com/nrdg/HBN-POD2.git

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 particular, this dataset contains two subdatasets, one for the QSIPrep derivative dataset in derivatives/qsiprep, and one for the AFQ derivative dataset in derivatives/afq. In order to retrieve file availability metadata in subdatasets, run

datalad get -n <path/to/subdataset>

For example, run

datalad get -n derivatives/qsiprep

or

datalad get -n derivatives/afq

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.