Naomi B. Robbins

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Naomi B. Robbins is the author of Creating More Effective Graphs, published by John Wiley (2005). She is a consultant, keynote speaker, and seminar leader who specializes in the graphical display of data. She trains employees of corporations and organizations on the effective presentation of data. She also reviews documents and presentations for clients, suggesting improvements or alternative presentations as appropriate. Naomi received her Ph.D. in mathematical statistics from Columbia University, M.A. from Cornell University, and A.B. from Bryn Mawr College. Dr. Robbins was an officer of the Statistical Graphics Section of the American Statistical Association (ASA). She has served the New Jersey Chapter of the ASA as President, Vice-President, Secretary, Treasurer, and Chair of the Advisory Committee, and was the first chapter member to be awarded the Chapter Service Award. She had a long career at Bell Laboratories before forming NBR, her consulting practice.

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Robbins, Naomi B.

35.7 Commentary by Naomi B. Robbins

Stephen Few wrote an excellent description of data visualization and the necessity for designing graphics to take advantage of our knowledge of human perception and cognition. In this commentary I question who is responsible for the myriad of visualizations that ignore this knowledge: the software vendors, the software users or others? In addition, I point out important work that deserves greater exposure on the integration of geo-spatial and other forms of data display, a topic on Few's most-needed list. I end with additional sources for learning more.

35.7.1 Responsibility for perceptual problems with many data visualizations

Few's article states:

Since the turn of the 21st century, data visualization has been popularized, too often in tragically ineffective ways as it has reached the masses through commercial software products.

Certainly, software vendors are responsible for offering many graph forms that hinder rather than help the reader to understand the data. The vendors offer graphs to wow the audience rather than to communicate clearly and they create demand for ineffective graphs. But they are not solely responsible for the myriads of graphs with perceptual problems.

People learn from what they see and they see many ineffective graphs. The software users then demand software that allows them to imitate these ineffective designs. This gets us in a chicken and egg situation: Do vendors produce these awful visualizations because their customers demand them, or do the customers become attracted to them when they see what vendors market?

An example of the ineffective ways includes pseudo-third dimensions in bar charts. Figure 1 shows a pseudo-three-dimensional bar chart in Excel. Almost no one reads it correctly. I describe other problems with this graph in Creating More Effective Graphs [1].

Almost no one reads this simple chart correctly. The numbers plotted are 1, 2, and 3. Plot it yourself in Excel if you don't believe me
Figure 35.1: Almost no one reads this simple chart correctly. The numbers plotted are 1, 2, and 3. Plot it yourself in Excel if you don't believe me

A number of graphic artists have made major contributions to the field of data visualization. However, there are some graphic artists who have no appreciation of numbers and don't realize that the representation of numbers in graphs should be proportional to the numbers they represent. As a result, it is common to see graphs that are not drawn to scale.

Some graph designers want to give the impression of better performance than is actually the case and intentionally design graphs that mislead to achieve this impression. Other graph designers may be more concerned with demonstrating their technological abilities or artistic abilities than in communicating clearly and accurately. Until recently, our educational system did not provide training in communicating numbers. Today, there are some excellent courses at the college level but the majority of people receive little, if any, training in presenting numerical information. Therefore, many graph designers are unaware of the principles of effective graphs. Some of the problems occur from a lack of proofreading and careless errors.

As an analogy, a current style in fashion is high-heeled shoes. A quick search on "dangers of high heels" revealed that there has been an increase in the number of bunion operations on wearers of high heels as well as foot pain, back pain and neck pain. In some cases the Achilles tendon grows shorter. Balance is affected so that the risk of falls is greater. The list of problems goes on and on. Is the shoe designer, the shoe manufacturer, the retail outlet that sells the shoes or the customer who buys them responsible for this increase in medical problems? Is this situation analogous to the data visualization one? Both cause serious problems: poor business decisions in one case and pain and suffering as well as unnecessary medical expenses in the other. I hope that these questions stimulate interesting discussion.

35.7.2 Integration of geo-spatial displays with other forms of display

In his section on future directions, Few mentions areas that offer the potential for enrichment including the integration of geo-spatial displays with other forms of display for seamless interaction and simultaneous use. Several researchers have made advances in this area. For example, the micromap designs of Dan Carr [1] and [2] add a geographic context to statistical information, allowing for the joint exploration of statistical and geographic patterns in data. As illustrated in Figure 2, statistical graphics, here dots, are linked to small maps by color. In the first row, we can see that Maryland is represented by red dots and so Maryland is shaded red on the right-hand map. Sorting by poverty level, we see that not only are poverty and education inversely related, but that there is a geographic clustering of southern U.S. states by these variables.

An example of a micromap design from Carr and Pickle [1]
Figure 35.2: An example of a micromap design from Carr and Pickle [1]

35.7.3 Where to Learn More

Data visualization does not belong to a single academic discipline. Statisticians, computer scientists, psychologists, graphic designers and others practice and contribute to data visualization. The university programs and resources that Few mentions lean heavily towards computer science. A few excellent programs joining statistical graphics with computer science are available at George Mason University, Iowa State, and the University of Augsburg. There are many others. I will leave it to other commentators to add excellent programs in cognitive psychology and graphic design. The Journal of Computational and Graphical Statistics, a joint publication of the American Statistical Association, the Institute of Mathematical Statistics and the Interface Foundation of North America is another academic journal on the topic. The Statistical Computing Statistical Graphics Newsletter (SCGN) is another informal publication. Although the Joint Statistical Meetings are not exclusively devoted to statistical graphics and data visualization, there are as many sessions sponsored by the Statistical Graphics Section as many a smaller conference contains.

One addition I would make to the "what's needed" list is better communication between the computer scientists, graphic designers, psychologists and statisticians. More joint conferences and attending each other's conferences would help each discipline benefit from the research of the others.

35.7.4 References

  1. Carr, Daniel B. and Linda Williams Pickle. 2010. Visualizing Data Patterns with Micromaps. Chapman and Hall/CRC, Boca Raton, FL.
  2. Carr DB, Wallin JF and Carr DA. Two new templates for epidemiology applications: Linked micromap plots and conditioned choropleth maps. Statistics in Medicine 19:2521-38, 2000.
  3. Robbins, Naomi B. 2005. Creating More Effective Graphs. John Wiley and Sons, Hoboken, NJ.