Digital data has no physical shape. While this allows us to manipulate easily great amounts of data, it poses a problem when it comes to understanding this data and assessing its state. The lack of physical shape renders useless our built-in skill of perceiving the world around us through visual stimuli.
Visualization aims to solve this problem by offering a visual skin to data. “A picture tells a thousand words” goes the old adage. And so it does, but only if the picture is the right one.
What makes a picture appropriate? Well, it has to focus on one or more relevant questions, and it has to take the particularities of data into account.
There are many tools out there providing nice and useful visualizations for interesting questions. However, many of them offer only limited customization possibilities, and this makes them less useful in particular circumstances.
The name Mondrian comes from the famous Dutch painter that used to see the world in rectangles and lines. In a similar manner, our Mondrian views data through a graph lens with nodes connected with each other via edges.
The rest of this chapter describes Mondrian in details. We start with a short example, and continue by introducing the concepts and the architecture and by detailing the important components.