1. Telling stories using visualization - visual primacy

It is almost impossible to talk about InfoVis without mentioning Tufte. His four books beautifully illustrate how to explain and present complex data using visual means. These books are certainly for designers, more specifically, info graphics designers. The approach can be summarized as: tell good stories with superb visual design. In most of the cases, the designers are very familiar with the data to be visualized, and they have a set of messages to convey to the graphics readers. To “transmit” the messages effectively, special attention is paid to the choices of visual metaphor, color, layout and even border thickness. Interactive features are great add-ons that make static graphics more appealing, and they allow readers to explore additional information that could not be included in an overview. In all cases, it seems fair to use an information processing metaphor to describe the design process: there is an intended information flow from the designers to the readers, with visualization being the medium or conduit. The success of design is measured by how effectively the intended message is received, and the readers are primarily cast as passive information processors, their minds often assumed as tabula rasa.

I would argue that much of the InfoVis research is modeled after this approach. This is especially true if we consider that many representation or interaction techniques are accompanied by illustrations showing “novel” insights revealed by clever design: “look! here’s a piece of information that’s more evidently presented!”. Whether this is something users already know, or want to know, is often overlooked.

2. Analyzing data using visualization - interaction primacy

Analyzing data using visualization (or “visual analytics”, in current buzzwords) is a very different activity, and I make a bold (well, sort of) claim that interaction, not visualization, should be the focal point of design. This doesn’t mean visual properties are not important, it just means that visual design is not sufficient and should be subsumed under a larger scope of interaction design. Here in the context of visual analytics, designers are not primarily info graphics designers, but interaction designers. They are not delivering visual displays but visual analytic tools. Often the designers have no access to end users’ data; even when they do, they are usually not sure what useful insights may exist in the data. There is clearly a less definitive message to convey — unless the designers are building a very specialized domain-specific tool. Insights, or messages must be “stumbled upon” and discovered by the users. There are hence two challenges that set interaction design apart from graphics design. First, users cannot be cast as passive information receivers, but active information seekers. Good visual designs do afford easier picking up of information, but a more important issue to be considered here is semantic distance: “how well does the interface support me to ask questions about the data?” Secondly and consequently, users’ ability of visual reasoning is a more important factor than visual properties in determining the outcome of the analysis. Traditional InfoVis research tends to overlook these issues, and I think they are an important part of visual analytics’ agenda.