An interesting article by Chaomei Chen, on the Top 10 Unsolved Information Visualization Problems. One of the unsolved problems is aesthetics:

The purpose of information visualization is the insights into data that it provides, not just pretty pictures. But what makes a picture pretty? What can we learn from making a pretty picture and enhancing the representation of insights? It’s important, therefore, to understand how insights and aesthetics interact, and how these two goals could sustain insightful and visually appealing information visualization.
The graph-drawing community has done the most advanced research in relation to the aesthetics problem. However, much of the aesthetics wisdom consists more of heuristics than empirical evidence at the elementary level of perceptual–cognitive tasks. There is a lack of holistic empirical studies to characterize what visual properties make users think a graph is pretty or visually appealing. Research in this area often focuses on graph-theoretical properties and rarely involves the semantics associated with the data.

Other points I found noteworthy: the need of a parading shift from the ability to visualize structure to the ability to visualize dynamics; the importance of expressing causality and inference in order to enable visual thinking and reasoning. (Also see: Tufte's Visual Explanations, and his forthcoming work, Beautiful Evidence).