@@ -17,7 +17,7 @@ easy accessible framework to visualize data from a GUI and the command line
 (and of course through a script).
 
 There exists nothing like that. Of course you can also work with software like
-Paraview via the built-in python shell. But, if you really want to explore your
+Paraview_ via the built-in python shell. But, if you really want to explore your
 data it is totally not straightforward to access and explore it from within
 such a software using numeric functions from numpy, scipy, etc.
 
@@ -26,8 +26,8 @@ efficiently with short and comprehensive commands, that can be accessed
 through a GUI (see :ref:`projects`) and where you have always a comprehensive
 API to access your data.
 
-Different from the usual use with matplotlib, which in the end most of the time
-results in copy-pasting parts of your code, this software is build on the
+Different from the usual use with matplotlib, which in the end results most of
+the time in copy-pasting parts of your code, this software is build on the
 *don't repeat yourself* principle. Each of the small parts that make up a
 visualization, whether it is part of the data evaluation or of the appearance
 of the plot, psyplot puts it into a formatoption can be reused when it is
@@ -41,6 +41,92 @@ please let me know if you have a different opinion.
 .. _matplotlib: http://matplotlib.org
 
 
+.. _what-it-is-and-what-it-is-not:
+
+What it is, and what it is not
+------------------------------
+.. note::
+
+    First of all, it's open source! So please, if you don't agree with the
+    points below, `edit this document`_ and click on *Propose File Change* and
+    *Create pull request*. We can then discuss your changes.
+
+.. _edit this document: https://github.com/psyplot/psyplot/edit/master/docs/about.rst
+
+There are tons of software tools around for visualization, so what is special
+about psyplot? The following list should hopefully provide you some guidance.
+
+What it is not
+**************
+- it is not the fastest. If matplotlib or the standard visualization utilities
+  from R, NCL, etc. are sufficient for you, you can go with psyplot. If you
+  want to create a global map with tens of millions of grid cells, you are
+  better of using a more powerful (but more complex and in many respects less
+  flexible) GPU-based software, such as Paraview_.
+- it is not the best for interactive web-applications. Although it would be
+  pretty simple to set up a backend server with psyplot and tornado_ or Flask_,
+  for instance, it's limited to sending rastered image data around, due to the
+  `options provided by matplotlib`_. This might change in the future, when we
+  are using `other visualization backends`_.
+- it is not as fast as ncview_. psyplot (and psy-view_ in particular) are
+  written in python and therefore, we are very flexible (much more than ncview),
+  but we will never beat the speed of the (compiled) ncview software.
+- our GUI is not the most interactive one. psyplot is a `command-line-first`
+  software, i.e. we put the most effort in making the usage from command-line
+  and scripts as easy as possible. The GUI is something on top and is limited by
+  the speed and functionalities of matplotlib (which is, nevertheless, pretty
+  rich)
+- it is not made for statistical visualizations. Although there are some
+  functionalities implemented by psy-reg_, it will never beat the possibilities
+  by packages like seaborn_ or R_. The only advantage of psy-reg over these
+  other software tools, is the possibility to adapt everything using the full
+  power of matplotlib artists within and outside of the psyplot framework
+- it is not the best software for manipulating shapefiles, although some support
+  of this might come in the future.
+
+What it is
+**********
+- It is fast. Not necessarily when it comes down to being the fastest
+  interactive visualization software, but for sure when it comes down to
+  development time, as it is very user-friendly from the command line. There are
+  no other software packages that provide a simple and intuitive visualization
+  such as
+
+  .. code-block:: python
+
+      psy.plot.mapplot('my-netcdf-file.nc', lonlatbox='Germany')
+
+  while still providing a very high range of flexible options to adjust the
+  visualization. No GUI, independent of it's intuitiveness, can ever beat the
+  speed of a scientist that knows a bit of coding and how to use the different
+  formatoptions in psyplot.
+- it is very flexible (I think we made this point already).
+
+  * We can implement tons of new visualization and data analysis techniques and
+    :ref:`you can implement your own <plugins_guide>`.
+  * they are automatically implemented in the GUI
+  * the user can do his statistical and numerical computations with software
+    like xarray, numpy, scipy, etc. and then use the psyplot visualization
+    methods in the same script
+  * it's modular framework allows to tackle new scientific questions and handle
+    handled them in separate psyplot plugins with it's own formatoptions and
+    plotting methods
+- it intuitively integrates the structure of netCDF files. So if you often
+  work with netCDF files, psyplot might be a good option
+- it is pythonic. If you are using python anyway, psyplot is worth a try and we
+  are always keen to help new users getting started.
+- it will always be free and open-source under the GPL License.
+
+.. _Paraview: https://www.paraview.org
+.. _tornado: https://www.tornadoweb.org
+.. _options provided by matplotlib: https://matplotlib.org/3.1.1/faq/howto_faq.html#how-to-use-matplotlib-in-a-web-application-server
+.. _other visualization backends: https://github.com/psyplot/psy-view
+.. _ncview: http://meteora.ucsd.edu/~pierce/ncview_home_page.html
+.. _psy-reg: https://psyplot.readthedocs.io/projects/psy-reg
+.. _seaborn: https://seaborn.pydata.org
+.. _R: https://www.r-project.org/
+
+
 About the author
 ----------------
 I, (`Philipp Sommer`_), work as a Data Scientist at the Helmholtz-Zentrum