Yogi Berra, in his unique grasp of the obvious, once said, “You can observe a lot by watching.” If you want to see - as in a spark of comprehension that evokes the statement “Aha, I see” - there is no better way than using your eyes. In recent years, a field of research and development has emerged to explore and exploit this fact, called information visualization. The timing is right - we now have huge storehouses of information rotting away because we don’t know how to make sense of them. Perhaps Edna St. Vincent Millay didn’t have the current state of the so-called information age in mind when she wrote this poem, but it nonetheless describes our situation today beautifully:
Upon this gifted age, in its dark hour,
falls from the sky a meteoric shower
of facts. They lie, unquestioned, uncombined.
Wisdom enough to leech us of our ill is daily spun;
but there exists no loom to weave it into fabric.
I believe that information visualization can serve as the loom that we so desperately need.
Information Visualization Defined
Technically speaking, information visualization, often shortened to infovis, does not refer to all forms and uses of visually represented information. For the full range of visual data representations, regardless of their nature or purpose, I use the term data visualization. Infovis is narrower in focus. Here’s the definition that was proposed by three prominent leaders in the field: Information visualization is the use of computer-supported, interactive, visual representations of abstract data to amplify cognition.1
By describing data as abstract, the authors were trying to set infovis apart from what they called “scientific visualization.” Information of all types can be shown visually, but some visualizations display things that have physical form, which the visualization replicates, such as an MRI scan of the human brain. Unlike scientific visualization, infovis displays information that is abstract in nature. Because it has no physical form to replicate, representations must be invented, using visual attributes such as size, shape and color to present it in ways that faithfully and meaningfully encode it. When a line graph is used to display the ups and downs of revenues and expenses through time, it paints a picture of something that is abstract.
Infovis is for one purpose only - to help us think more effectively about information in an effort to understand it. The whole point is to use graphical representations and interactions with them to take advantage of visual perception’s unique ability to recognize and make sense of patterns, and to augment our brains in ways that are designed to work around some of their limitations. Why present information visually? Not to make it more entertaining. Certainly not to make it pretty. There is only one reason why we should do this: to bring to light meanings in data that might remain hidden from view if displayed in other ways, such as tables of text. When pictures can tell the story better than any other means, visualization is the proper mode of display.
Milestones in Infovis Development
Visual representations of abstract information have been around longer than infovis, which emerged as an academic discipline in the last 20 years. We owe thanks to the 17th century philosopher and mathematician René Descartes for the original innovation that has led to most of today’s graphs. Descartes introduced the use of a 2-D set of perpendicularly arranged X and Y axes, each marked from one end to the other with scales to form a coordinate system that could be used to represent quantitative data. Unlike most of the 2-D graphs that we now use primarily to present data, Descartes invented this form of display to perform mathematics.
A Scottish fellow named William Playfair in the late 18th and early 19th centuries popularized the use of 2-D graphs for communicating quantitative data. He invented or dramatically improved many of the graphs that we take for granted today, such as bar graphs and pie charts.
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