In many previous blog posts I talked about my experiments in flow mapping (exhibit 1, exhibit 2 ...). Usually this was about migration or commuting data and in the course of writing an academic paper on the subject I also put together a small website about flow mapping, with some examples. Now I've done a follow-up paper to this which is just out in Environment and Planning B (a couple of extracts shown below).
The point of this work is not simply to make pretty pictures. That might be an interesting by-product but it is more about the process of taking data and giving it some kind of meaning by mapping it. This is by no means trivial when you're looking at migration or commuting patterns which link hundreds or even thousands of places.
With this much data, you often have millions of individual cells of data, so making sense of it can be impossible without some kind of visual approach - and that's really what the paper is about. It's not really very complicated - at least, not conceptually - but the power of this type of approach is in its ability to generate knowledge from raw data.
In short, then, this kind of work is in many ways guided by Kenneth Boulding's maxim that "knowledge is always gained by the orderly loss of information".
