Merge pull request #1178 from datalad-handbook/fixes

Fixes

docs/basics/101-117-sharelocal2.rst

@@ -36,7 +36,7 @@ Before getting another PDF, let's query git-annex where its content is stored:
    $ cd ../mock_user/DataLad-101
    $ git annex whereis books/TLCL.pdf
 
-Oh, another cryptic character sequence - this time however not a symlink, but a :term:`annex UUID`.
+Oh, another cryptic character sequence - this time however not a symlink, but an :term:`annex UUID`.
 "That's hard to read -- what is it?" your room mate asks.
 You can recognize a path to the dataset on your computer, prefixed with the user and hostname of your computer.
 "This", you exclaim, excited about your own realization, "is my dataset's location I'm sharing it from!"
@@ -82,8 +82,8 @@ The message further informs you that there is only "``(1 copy)``" of this file c
 This makes sense: There is only your own, original ``DataLad-101`` dataset in which this book is saved.
 
 To retrieve file content of an annexed file such as one of these PDFs, git-annex will try to obtain it from the locations it knows to contain this content.
-It uses the checksums to identify these locations.
-Every copy of a dataset will get a unique ID with such a checksum.
+It uses the UUID to identify these locations.
+Every copy of a dataset will get a UUID as a unique identifier.
 Note however that just because git-annex knows a certain location where content was once it does not guarantee that retrieval will work.
 If one location is a USB stick that is in your bag pack instead of your USB port, a second location is a hard drive that you deleted all of its previous contents (including dataset content) from,
 and another location is a web server, but you are not connected to the internet, git-annex will not succeed in retrieving contents from these locations.

docs/basics/101-132-advancednesting.rst

@@ -45,9 +45,9 @@ From the superdataset's perspective, the subdataset appears as being
 indeed the complete subdataset as a single entity.
 
 What this shows you is that the modifications of the subdataset you performed are not
-automatically recorded to the superdataset. This makes sense -- after all it
-should be up to you to decide whether you want record something or not --,
-but it is worth repeating: If you modify a subdataset, you will need to save
+automatically recorded to the superdataset. This makes sense, after all it
+should be up to you to decide whether you want record something or not.
+But it is worth repeating: If you modify a subdataset, you will need to save
 this *in the superdataset* in order to have a clean superdataset status.
 
 Let's save the modification of the subdataset into the history of the

docs/basics/101-133-containersrun.rst

@@ -56,7 +56,7 @@ others. On your own and other's machines, the container constitutes a secluded
 software environment that
 
 - contains the exact software environment that you specified, ready to run
-  analyses in
+  analyses
 - does not effect any software outside of the container
 
 Unlike virtual machines, software containers do not have their own operating
@@ -104,7 +104,7 @@ Singularity (even without having Docker installed).
 
 .. importantnote:: Additional requirement: Singularity
 
-   In order to use Singularity containers you have to
+   To use Singularity containers you have to
    `install <https://docs.sylabs.io/guides/3.4/user-guide/installation.html>`_ the software singularity.
 
 .. index::
@@ -129,7 +129,7 @@ Using ``datalad containers``
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 One core feature of the ``datalad containers`` extension is that it registers
-computational containers to a dataset. This is done with the
+computational containers with a dataset. This is done with the
 :dlcmd:`containers-add` command.
 Once a container is registered, arbitrary commands can be executed inside of
 it, i.e., in the precise software environment the container encapsulates. All it
@@ -193,14 +193,14 @@ name to give to the container, and a path or URL to a container image:
    pair: hub; Docker
 .. find-out-more:: How do I add an image from Docker-Hub, Amazon ECR, or a local container?
 
-   Should the image you want to use lie on Dockerhub, specify the ``--url``
+   Should the image you want to use sit on Dockerhub, specify the ``--url``
    option prefixed with ``docker://`` or ``dhub://`` instead of ``shub://``:
 
    .. code-block:: console
 
       $ datalad containers-add midterm-software --url docker://adswa/resources:2
 
-   If your image exists on Amazon ECR, use a ``dhub://`` prefix followed by the AWS ECR URL as in
+   If your image lives on Amazon ECR, use a ``dhub://`` prefix followed by the AWS ECR URL as in
 
    .. code-block:: console
 

docs/basics/101-136-filesystem.rst

@@ -454,7 +454,7 @@ convenient. It can be a confusing and potentially "file-content-losing"-dangerou
 process, but it also dissociates a file from its provenance that is captured
 in its previous dataset, with no machine-readable way to learn about the move
 easily. A better alternative may be copying files with the :dlcmd:`copy-file`
-command introduced in detail in the web version, and demonstrated in the next
+command introduced in detail in the online-handbook, and demonstrated in the next
 but one paragraph. Let's quickly clean up by moving the file back:
 
 .. runrecord:: _examples/DL-101-136-137
@@ -619,7 +619,7 @@ provenance record is lost:
 Nevertheless, copying files with :dlcmd:`copy-file` is easier and safer
 than moving them with standard Unix commands, especially so for annexed files.
 A more detailed introduction to :dlcmd:`copy-file` and a concrete
-use case can be found in the online version of the handbook.
+use case can be found in the online-handbook.
 
 Let's clean up:
 
@@ -1023,7 +1023,7 @@ private :term:`SSH key`\s or passwords, or too many or too large files are
 accidentally saved into Git, and *need* to get out of the dataset history.
 The command ``git-filter-repo <path-specification> --force`` will "filter-out",
 i.e., remove all files **but the ones specified** in ``<path-specification>``
-from the dataset's history. An advanced chapter in the online version of the handbook
+from the dataset's history. An advanced chapter in the online-handbook
 shows an example invocation.
 
 .. index::

docs/basics/101-141-push.rst

@@ -183,5 +183,5 @@ For more information on this, and other error messages during push, please check
 .. rubric:: Footnotes
 
 .. [#f1]  RIA siblings are file system based, scalable storage solutions for
-          DataLad datasets. You can find out more about them in the online version.
+          DataLad datasets. You can find out more about them in the online-handbook.
 .. [#f2] For information on the ``numcopies`` and ``wanted`` settings of git-annex see its documentation at `git-annex.branchable.com/git-annex-wanted/ <https://git-annex.branchable.com/git-annex-wanted>`_ and `git-annex.branchable.com/git-annex-numcopies/ <https://git-annex.branchable.com/git-annex-numcopies>`_.

docs/basics/101-146-gists.rst

@@ -171,7 +171,7 @@ In order to back-up datasets you can publish them to a
 solution does not require Git, git-annex, or DataLad to be installed on the
 machine that the back-up is pushed to, the latter does require them.
 
-To find out more about RIA stores, checkout the online version of the handbook.
+To find out more about RIA stores, checkout the online-handbook.
 A sketch of how to implement a sibling for backups is below:
 
 .. code-block:: console

docs/glossary.rst

@@ -143,7 +143,7 @@ Glossary
       .. index::
          pair: extension; DataLad concept
 
-      Python packages that equip DataLad with specialized commands. The online version of the handbook has an entire chapter that
+      Python packages that equip DataLad with specialized commands. The online-handbook has an entire chapter that
       gives an overview of available extensions contains demonstrations.
 
    DataLad Gooey

docs/intro/installation.rst

@@ -14,7 +14,7 @@ Install DataLad
    The installation methods presented in this chapter are based on experience
    and have been tested carefully. However, operating systems and other
    software are continuously evolving, and these guides might have become
-   outdated. Be sure to check out the online version for up-to-date information.
+   outdated. Be sure to check out the online-handbook for up-to-date information.
 
 In general, the DataLad installation requires Python 3 (see the
 :find-out-more:`on the difference between Python 2 and 3 <fom-py2v3>` to learn