This is a book about visualization, and specifically the presentation of data in visual form. One can think of visualization as a kind of transformation that takes information in a form suitable for computation into forms more compatible with human perception and cognition and more easily communicated. The current book is an introduction to the subject. It is aimed at graduate students and advanced undergraduates in computer science, but it would be accessible to a much broader audience.
Visualization is a young field with only a few primary texts available. What distinguishes this one is the way it synthesizes past work to develop a comprehensive framework for design and analysis. Edward Tufte’s books, especially Envisioning Information, were eye-opening to many of us involved in preparing data for analysis, talks, reports and papers. But Tufte concentrated on static design presentations and there are now many new possibilities for interactive and dynamic graphical data analysis and presentation.
The author builds a framework for understanding the key elements of visualization and develops a synthesis of current best practices. She breaks down the framework for analysis into three steps: what, why and how. “What” addresses the kind of data that is to be visualized; “why” identifies the purposes for creating the visualization; “how” describes the method by which it is carried out. In this book, the “what” includes three generic data types: tables, spatial data, and networks. The table category includes scatterplots, bar charts, dot and line charts, heat maps and pie charts. Maps, vector, tensor and flow fields are spatial data. Networks include tree structures and adjacency matrix views.
The first part of the book addresses the what, why and how questions in detail and then considers the validation question: how well does a particular visualization actually work? This leads naturally into a discussion of visual channels; these are the means of controlling the basic graphical elements in an image. Channels include spatial position, length, angle, area, depth, color, curvature, volume, shape, and motion. Matching the channel to the human perceptual system is a key to effective visualization design. As a simple example, think of pie charts and bar charts. Pie charts require both angle and area judgments, which are perceptually harder and less accurate than bar charts that require only judgments of length on a common scale.
One of the most useful chapters to a casual reader is on rules of thumb for visualization. These include: don’t use 3D when 2D will do, and don’t use 2D when a one-dimensional list will do. Using our eyes to switch between two views that are visible simultaneously has a much lower cognitive load than relying on memory to compare a current view with one seen before… There are about half a dozen similar rules presented in the book. They are perceptive and clearly based on years of experience.
The book is filled with examples from the universe of visualization. Virtually all the possibilities for visualization design are illustrated with specific examples.
It’s also worth pointing out what’s not in the book. The author intentionally takes a top-down look at visualization. This does not extend all the way to the level of algorithms. As the author notes, the book is already pretty long and would need to double in size to incorporate an adequate treatment of algorithms. On a more fundamental level, the book is about visualization of data, not about visualization in the broader sense that mathematicians sometimes use. So there is no visualization of the hypercube here, no eversion of the sphere, not anything like that.
This is an attractive book, one that’s likely to be a fundamental source for the field. It’s worth a look for anyone with even a passing interest.
Bill Satzer (firstname.lastname@example.org) is a senior intellectual property scientist at 3M Company, having previously been a lab manager at 3M for composites and electromagnetic materials. His training is in dynamical systems and particularly celestial mechanics; his current interests are broadly in applied mathematics and the teaching of mathematics.