Add a quick start section to the documentation

installation.md

@@ -8,6 +8,7 @@ Table of Contents
 =================
 
   * [Prerequisites](#prerequisites)
+  * [Quick start](#quick-start)
   * [Data preparation](#data-preparation)
 
 ## Prerequisites
@@ -36,11 +37,39 @@ To this end run the following command in R or RStudio.
 
 To get started with the guide you will have to download our [prepared package](link.to.package) or clone the [github repository](github.com).
 In the remainder of this guide we will assume that the package is extracted in
-your home directory: `~/icobire-guide/`.
+your home directory: `~/ICoVeR/`.
+
+## Quick start
+
+The easiest way to get started with ICoVeR is by installing the package with the pre-loaded CSTR data set.
+This data is already in the repository under [R.ICoVeR/data](https://github.com/bbroeksema/ICoVeR/tree/master/R.ICoVeR/data).
+To install ICoVeR open [R.ICoVeR/ICoVeR.Rproj](https://github.com/bbroeksema/ICoVeR/blob/master/R.ICoVeR/ICoVeR.Rproj) in RStudio and use the "build and reload" button in the build tab (top right of the screen).
+Alternatively. use an R-session to install the ICoVeR package:
+
+{% highlight r %}
+
+# This assumes the workdirectory is ~/ICoVeR (or the actual location on your 
+# machine where ICoVeR was checked out)
+library(devtools)
+install_local(file.path(getwd(), "R.ICoVeR"))
+
+{% endhighlight %}
+
+After installation you must start OpenCPU and launch the browser:
+
+{% highlight r %}
+
+# Start opencpu and launch ICoVeR in the browser
+library(opencpu)
+opencpu$stop() # It starts at a random port, which is annoying.
+opencpu$start(8000)
+browseURL("http://localhost:8000/ocpu/library/ICoVeR/www/", browser = getOption("browser"), encodeIfNeeded = FALSE)
+
+{% endhighlight %}
 
 ## Data preparation
 
-In order to get you started quickly with the tool, we [provide]() to prepared datasets.
+In order to get you started quickly with the tool, we provide two prepared datasets.
 The first data set is the one generated by [Wrighton et al](http://www.sciencemag.org/content/337/6102/1661).
 The second data set, is the CSTR data set, which is generated by us from an anaerobic digester.