.. _summary_nest:

Summary
-------

In the last two sections, we have discovered the basics of installing a published DataLad dataset,
and experienced the concept of modular nesting datasets.

* A published dataset can be installed with the :command:`datalad install` command:
  :command:`datalad install [--dataset PATH] --source PATH/URL PATH`.

* The command takes a location of an existing dataset (``--source``/``-s``),
  and a path to where you want the dataset to be installed. If you do not specify a path,
  the dataset will be installed in the current directory, with the original name of the
  dataset you are installing.

* If a dataset is installed inside of a dataset, the ``--dataset``/``-d`` option
  needs to specify the root of the superdataset.

* The source can be a URL (for example of a Github repository, as in section :ref:`installds`), but also
  paths, or open data collections.

* After installation, only small files and metadata about file availability are present locally.
  To retrieve actual file content of larger files, :command:`datalad get PATH` downloads large file
  content on demand.

* :command:`datalad status --annex` or :command:`datalad status --annex all` are helpful to determine
  total repository size and the amount of data that is present locally.

* Remember: Super- and subdatasets have standalone histories. A superdataset only stores
  which version of the subdataset is currently used.


Now what I can do with that?
^^^^^^^^^^^^^^^^^^^^^^^^^^^^

You have procedurally experienced how to install a dataset, but simultaneously you have
learned a lot about the principles and features of DataLad datasets.
Installing datasets and getting their content allows you to consume published datasets.
By nesting datasets within each other, you can modular re-use datasets. While this may
appear abstract, upcoming section will demonstrate many example of why this can be handy.

