Laura Waite
0b3a27f295
Content from the DataLad Handbook http://handbook.datalad.org/en/latest/basics/101-180-FAQ.html#how-can-i-help-others-get-started-with-a-shared-dataset
101 lines
4.1 KiB
Text
101 lines
4.1 KiB
Text
An Extension of studyforrest.org Dataset
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Multi-resolution 3T fMRI data on the representation of visual orientation
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=========================================================================
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This dataset consists of empirical 3T fMRI data recorded at three spatial
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resolutions (1.4 mm, 2 mm, and 3 mm isotropic voxel size) for orientation
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decoding in visual cortex — in order to test hypotheses on the strength and
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spatial scale of orientation discriminating signals. This is an extension of
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the studyforrest project. All seven participants previously volunteered for the
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audio-only and the audio-visual Forrest Gump study.
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Five of the seven participants also participated in a matching study using
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identical protocols, but 7T data acquisition (with the same the three spatial
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resolutions used here, plus a 0.8 mm acquisition). The dataset is compliant
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with the BIDS data description standard (http://bids.neuroimaging.io). A
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detailed description can be found in:
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Sengupta, A., Speck, O., Yakupov, R., Kanowski, M., Tempelmann, C.,
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Pollmann, S. & Hanke, M. (2018) The effect of acquisition resolution on
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orientation decoding from V1: comparison of 3T and 7T. bioRxiv.
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https://doi.org/10.1101/305417
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For more information about the project visit: http://studyforrest.org
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How to obtain the data files
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----------------------------
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This repository is a `DataLad <https://www.datalad.org/>`__ dataset. It provides
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fine-grained data access down to the level of individual files, and allows for
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tracking future updates. In order to use this repository for data retrieval,
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`DataLad <https://www.datalad.org>`_ is required.
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It is a free and open source command line tool, available for all
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major operating systems, and builds up on Git and `git-annex
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<https://git-annex.branchable.com>`__ to allow sharing, synchronizing, and
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version controlling collections of large files. You can find information on
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how to install DataLad at `handbook.datalad.org/en/latest/intro/installation.html
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<http://handbook.datalad.org/en/latest/intro/installation.html>`_.
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Get the dataset
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^^^^^^^^^^^^^^^
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A DataLad dataset can be ``cloned`` by running::
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datalad clone <url>
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Once a dataset is cloned, it is a light-weight directory on your local machine.
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At this point, it contains only small metadata and information on the
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identity of the files in the dataset, but not actual *content* of the
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(sometimes large) data files.
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Retrieve dataset content
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^^^^^^^^^^^^^^^^^^^^^^^^
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After cloning a dataset, you can retrieve file contents by running::
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datalad get <path/to/directory/or/file>
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This command will trigger a download of the files, directories, or
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subdatasets you have specified.
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DataLad datasets can contain other datasets, so called *subdatasets*. If you
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clone the top-level dataset, subdatasets do not yet contain metadata and
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information on the identity of files, but appear to be empty directories. In
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order to retrieve file availability metadata in subdatasets, run::
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datalad get -n <path/to/subdataset>
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Afterwards, you can browse the retrieved metadata to find out about
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subdataset contents, and retrieve individual files with ``datalad get``. If you
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use ``datalad get <path/to/subdataset>``, all contents of the subdataset will
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be downloaded at once.
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Stay up-to-date
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^^^^^^^^^^^^^^^
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DataLad datasets can be updated. The command ``datalad update`` will *fetch*
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updates and store them on a different branch (by default
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``remotes/origin/master``). Running::
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datalad update --merge
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will *pull* available updates and integrate them in one go.
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Find out what has been done
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^^^^^^^^^^^^^^^^^^^^^^^^^^^
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DataLad datasets contain their history in the ``git log``.
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By running ``git log`` (or a tool that displays Git history) in the dataset or on
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specific files, you can find out what has been done to the dataset or to individual files
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by whom, and when.
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More information
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^^^^^^^^^^^^^^^^
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More information on DataLad and how to use it can be found in the DataLad Handbook at
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`handbook.datalad.org <http://handbook.datalad.org/en/latest/index.html>`_. The
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chapter "DataLad datasets" can help you to familiarize yourself with the
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concept of a dataset.
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