Once you have a basic graph with a reasonable layout, applying visual attributes is the next step. In a business environment, there is often much more data about nodes and edges, such as age, income, gender, frequency of purchases, type of relationship, strength of relationship, and so on. These can be perceived by using visual attributes such as colors, line widths, sizes, labels, and so on. Choosing the right visual attribute takes advantage of our human perception. For example, a bright red item pops out from gray ones, or larger items are more visually dominant than small items.
Following are some important attributes examined in this chapter:
- Node attributes—Not all nodes are the same. Which has the most connections? Which is the oldest? Which has the biggest change? Use visual attributes such as color and size to reveal node data.
- Link attributes—Which links have the strongest connections? What are the different types of links? In what direction do the links point? Visual attributes such as color, line width, and arrows show link data.
- Labels—Who is that? What is that node? Perhaps one of the most important elements (particularly in smaller graphs), labels should not be an afterthought, but carefully planned so that they are clear, legible, and informative.
Consider a portion of the e-mail visualization discussed in the previous chapters. Figure 5-1 shows a subset that represents people in the family of one of the authors e-mailing each ...