Report from VisWeek 2011: Is information visualization a science?
Almost every year at VisWeek there is a panel, workshop, or presentation or two that asks the questions, “Is visualization a science?” or “Can we distinguish good visualizations from bad?” I’m frustrated by the fact that we still need to ask these questions. As the field of visualization continues to grow and struggles to mature, we increasingly recognize the ways in which it lacks discipline. We fear that visualization will wander somewhat aimlessly in fits and starts as we search for a more defined sense of what we’re trying to accomplish and better guidelines for doing it well.
This year’s instance of this was a panel of presentations on the topic “Theories of Visualization — Are There Any?” Two members of the panel, Colin Ware and Jarke Van Wijk, both expressed the opinion that visualization is not a distinct science, and should not be, but an interdisciplinary application of many sciences. Visualization, rather than a science in its own right, is more like design and engineering, which builds a bridge between science and the real world, primarily through technologies that help us think and communicate visually to solve real problems.
Given this premise, it necessarily follows that the merits of visualization should be determined by its ability to solve real problems and to do so in the most effective way possible. Can this be done? Why are we still asking this question? Of course it can be done. Testing the outcomes of a particular visualization or visualization system, if it has clear goals, is relatively straightforward. Unfortunately, this is rarely done, which is perhaps why we still feel like we must continue asking if it can be done. Beyond testing outcomes in a specific way (it worked fairly well for these particular subjects for this particular task under these particular conditions), it would be even more helpful if we could test the merits of a visualization in a more generalizable manner, thereby extending findings to a broader range of applications.
I look forward to the day when we all agree that visualization should be informed by good science and should be evaluated by its ability to solve real problems, so we can spend most of our time and energy doing that without hesitation. Yesterday, I attended a well-deserved tribute to George Robertson, one of the great pioneers in the field. George, who recently retired from Microsoft Research, originally coined the term “information visualization.” I was touched when he told us that, after many years of working in various aspects of computer science beginning in the 1960s, he eventually settled on information visualization because he wanted to do something that improved the lives of people. We who work in this field, like George, have a wonderful opportunity to do something that matters, something that makes the world a better place. For this reason, it’s a travesty when time is wasted covering the same old territory over and over, or frittered away on poorly designed research or on research that can’t possibly matter. People throughout the world in organizations of all types are waiting for us to give them the means to see more clearly. Those who see information visualization as a way to open the eyes of the world to greater understanding will do great work, because it matters.
Take care,
2 Comments on “Report from VisWeek 2011: Is information visualization a science?”
I agree and will take it further. It’s so sad that focus is on whether we have a science or not, or whether there can be. Of course we want and are evolving a science so as to perform predictions. There are many sciences and we are an infant compared to many of these (physics, mathematics, chemistry, …). And in fact our field is called computer science.
Enough said. I am a computer scientist, and I and my students work on visualization (science and applications).
Why asking wether it is a science or not. A university in Austria is testing “normal” designed Information visualization and well designed ones with an eye-tracking system to meassure the effect on answering specific questions based on the shown information. The result: it works! The quality of the answers is better and the time finding the answers is shorter. The science is to find out what works best.