diff --git a/docs/source/install/kernel_install.rst b/docs/source/install/kernel_install.rst
index fa35b7a..3ba1e41 100644
--- a/docs/source/install/kernel_install.rst
+++ b/docs/source/install/kernel_install.rst
@@ -3,14 +3,13 @@
 Kernel Installation
 -------------------
 
-IPython can be installed (different python versions, virtualenv or conda environments) can
-be installed as a kernel by following these steps:
+IPython can be installed (different python versions, virtualenv or conda 
+environments) as a kernel by following these steps:
 
 * make sure that the desired python installation is active (e.g. activate the environment)
   and ipython is installed
 * run once ``ipython kernelspec install-self --user`` (or ``ipython2 ...`` or ``ipython3 ...``
   if you want to install specific python versions)
 
-The last command installs a kernel spec file for the current python installation in
-``~/.jupyter/kernels/``. Kernel spec files are JSON files, which can be viewed and changed with a
+The last command installs a :ref:`kernel spec <jupyterclient:kernelspecs>` file for the current python installation. Kernel spec files are JSON files, which can be viewed and changed with a
 normal text editor.
diff --git a/docs/source/interactive/index.rst b/docs/source/interactive/index.rst
index 810b566..b155847 100644
--- a/docs/source/interactive/index.rst
+++ b/docs/source/interactive/index.rst
@@ -6,11 +6,12 @@ Using IPython for interactive work
    :maxdepth: 2
 
    tutorial
-   tips
-   reference
    magics
-   shell
+   plotting
    qtconsole
+   reference
+   shell
+   tips
 
 .. seealso::
 
diff --git a/docs/source/notebook/plotting.rst b/docs/source/interactive/plotting.rst
similarity index 90%
rename from docs/source/notebook/plotting.rst
rename to docs/source/interactive/plotting.rst
index b7e6324..5aafda0 100644
--- a/docs/source/notebook/plotting.rst
+++ b/docs/source/interactive/plotting.rst
@@ -2,7 +2,7 @@
 
 Plotting
 --------
-One major feature of the Jupyter notebook is the ability to display plots that 
+One major feature of the IPython kernel is the ability to display plots that 
 are the output of running code cells. The IPython kernel is designed to work 
 seamlessly with the matplotlib_ plotting library to provide this functionality.
 
@@ -21,7 +21,7 @@ requested using, for example::
 
 A particularly interesting backend, provided by IPython, is the ``inline``
 backend.  This is available only for the Jupyter Notebook and the
-:ref:`IPython QtConsole <qtconsole>`.  It can be invoked as follows::
+:ref:`Jupyter QtConsole <qtconsole>`.  It can be invoked as follows::
 
   %matplotlib inline
 
@@ -32,3 +32,5 @@ resulting plots will then also be stored in the notebook document.
 .. seealso::
 
     `Plotting with Matplotlib`_  example notebook
+
+.. include:: ../links.txt