A Ménage à Trois of Data, Eyes and Mind

Published
  • January 02 2008, 4:07pm EST

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.

 

In his efforts to report the political and economic realities of late 18th century England, which he published as the book The Commercial and Political Atlas (London, 1786), Playfair realized that much of this information could be best understood by his readers if it were presented visually. He wrote: “Information, that is imperfectly acquired, is generally as imperfectly retained; and a man who has carefully investigated a printed table, finds, when done, that he has only a very faint and partial idea of what he has read; and that like a figure imprinted on sand, is soon totally erased and defaced.”

 

After Playfair, graphs gradually became commonplace. The potential of visual representations, not just to communicate information, but also to help people explore and make sense of information, found its first great advocate in a Princeton statistician named John Tukey. As a statistician, Tukey used mathematics to find, confirm, describe and sometimes predict relationships between quantitative values. He recognized, however, that there are times when the meaning of numbers is best discovered and grasped by using our eyes and examining visual representations of those numbers to spot and analyze patterns. In 1977, Tukey wrote the book Exploratory Data Analysis (Addison-Wesley) to advocate this complementary approach to traditional statistics and to also introduce several new graphs that were needed to support the effort, including box plots. Tukey explained one of the great benefits of visualization over purely conventional statistical methods as: “The greatest value of a picture is when it forces us to notice what we never expected to see.”

 

Tukey was looking for ways to make information “more easily and effectively handleable by minds.” He anticipated a day when computers would be used to explore and interact with data visually, which in his day did not yet exist.

 

The seeds that Playfair sowed more than 200 years ago and Tukey adapted for exploring and analyzing data 30 years ago have since been nourished by several others. Many software vendors today claim involvement in information visualization.

 

Unfortunately, with the exception of a few mostly small software vendors that have emerged as byproducts of academic work, most software companies that claim visualization capabilities fail to live up to the name. Without expertise in the field, vendors create products that only superficially mimic characteristics of information visualization and accentuate flashy visual effects that are worse than useless, for they actually undermine the information and its use.

 

Today we stand on a molehill of what information visualization will eventually grow to become, surrounded by pools of quicksand that lure people into the mire of dysfunctional visualization products. Too many of today’s products are cheap imitations that thwart the promise of infovis, casting a shadow over the good work that is being done.

 

Keep in mind that the primary reason for infovis is to help people think about information in an effort to find what’s meaningful and make sense of it. When information is visualized properly, the result is what Joseph Berkson called an “interocular traumatic impact”: an insight that hits us between the eyes.

 

Colin Ware of the University of New Hampshire, an expert in visual perception and how information can effectively be represented visually, eloquently describes the unique power of visual perception for examining data:

 

Why should we be interested in visualization? Because the human visual system is a pattern seeker of enormous power and subtlety. The eye and the visual cortex of the brain form a massively parallel processor that provides the highest-bandwidth channel into human cognitive centers. At higher levels of processing, perception and cognition are closely interrelated, which is the reason why the words “understanding” and “seeing” are synonymous. However, the visual system has its own rules. We can easily see patterns presented in certain ways, but if they are presented in other ways, they become invisible.2

 

Visual representations of information can look impressive, entertaining us with flashy effects that excite you as much as those in the original Star Wars movie, but if they don’t help us think about the data in meaningful ways, it isn’t information visualization. When it works, our eyes are drawn to meaningful aspects of the data, clearly and accurately represented, that lead us to wonder, “What’s going on here?” which you can immediately investigate by interacting with the data, such as by zooming in to take a closer look and filtering out what’s irrelevant.

 

A few good products that demonstrate the strengths of infovis are now establishing a presence in the business place, including Tableau from Tableau Software, Spotfire DecisionSite and Spotfire DXP from TIBCO, JMP from SAS and Advizor Analyst from Advizor Solutions. Unlike these good examples, however, many so-called visualization products are poorly designed or miss the mark entirely. They misunderstand how information visualization works - how visualizations must be designed to utilize the strengths of visual perception and to augment cognition - sometimes resulting in products that not only work poorly, they don’t work at all. To put this into perspective, just think back to the early days of the Internet and remember how poorly most Web sites were designed.

 

Business intelligence (BI) vendors are now paying attention to infovis. They are beginning to see that traditional methods of data analysis involving tabular text-based displays are extremely limited. They must now take the time to study infovis and learn from the experts before developing products that claim to support it. As software consumers begin to recognize the difference between superficially cute visualizations and those that actually enlighten, vendors will no longer be able to feed their customers cheap candy in place of the nourishment they actually need. As vendors embrace infovis in an informed manner, the intelligence that BI has always promised might finally be within reach.

 

Don’t be fooled by dazzle over effectiveness or entertainment over usefulness. Take the time to step back and ask, “Does it really work and does it really matter?” Use your eyes. They’re more powerful than most of us realize.

 

References:

 

  1. Stuart K. Card and Jock D. Mackinlay. Readings in Information Visualization: Using Vision to Think. Morgan Kaufmann Publishers: 1999.
  2. Colin Ware. Information Visualization: Perception for Design. Morgan Kaufmann Publishers: 2004.

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