VisualComplexity has a link and abstract to work being done to simplify very complex graphical displays. I also scanned and read part of the original (very) technical paper. The paper was not quite what I expected, less directly practical, but did make me think about cases where I have had to work with very densely connected, generated graphs. The large scale relationship patterns can be seen but are hard to leverage. The visual results can be very strikingly beautiful in a mathematical sense. The beauty of the visualization, however striking, is usually not very useful. Algorithms can traverse the results, aggregate results and come up with conclusions. Our brains and visual systems have a much harder time with multi-dimensional spaces. Thus the pressure to simplify.
We think at most in 3D, and even then rather poorly. Even mundane business data quickly bubbles into many dimensions and the best you can do is slice it into pieces that themselves need to be categorized. Packages like Spotfire and Miner3D give you a chance at making sense of the results, but it is easy to spin off in a realm that is incomprehensible to business users. We did experiments with virtual world means to explore data, but there is little improvement when immersing yourself in the data. Still looking for solutions.
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