Thomas Lumley on R.
One of the strengths and weaknesses of the topic map standardization effort was that it presumed you already had a topic map.
A strength because the methods for arriving at a topic map remain unbounded and unsullied by choices (and limitations) of languages, approaches, etc.
A weakness because the topic map novice is left in the position of a tourist who marvels at a medieval cathedral but has no idea how to build one themselves. (Well, ok, perhaps that is a bit of a stretch. )
The fact remains there is are ever increasing amounts of data becoming available, many of which are just crying out for topic maps to be built for their navigation.
R is one of the currently popular data mining languages that can be pressed into service for the exploration of data and construction of topic maps.
Definitely a resource to explore and exploit before you invest in any of the printed R reference materials.