We reside in the information age and the era of big data. Information permeates our daily lives. Every conceivable piece of information is a swipe, click or tap away. Processing the wealth of data available is a chore for people, and it poses a challenge for communication professionals. How to communicate the numbers so people understand the story the numbers represent?
Visualizing data draws the eye and helps viewers see patterns and digest numbers. To penetrate through the mass of information and reach an audience, communication professionals need to tell a story. People respond to anecdotes and stories because they build empathy. If people can relate, they can retain. Visuals tell a story. They paint a picture.
To find the story in data, it’s necessary to think about data beyond numbers. Nathan Yau explains in Data Points, “Data is more than numbers, and to visualize it, you must know what it represents. Data represents real life. It’s a snapshot of the world in the same way that a photograph captures a small moment in time.”
Data visualization is the term for the graphical representation of data or information. The strength of visualization is the capability of making a large amount of information digestible at once. Think about the volume of infographics people are exposed to everywhere they go—the office, school, doctor’s office or the gym—we can’t escape them.
Edward Tufte wrote, in The Visual Display of Quantitative Information, “Modern data graphics do much more than simply substitute for small statistical tables. At their best, graphics are instruments for reasoning about quantitative information. Often the most effective way to describe, explore, and summarize a set of numbers—even a very large set—is to look at pictures of those numbers. Furthermore, of all methods for analyzing and communicating statistical information, well-designed data graphs are usually the simplest and at the same time the most powerful.”
The Interaction Design Foundation enumerated the following three common visualization uses:
- Presentation (educational or persuasive purposes)
- Explorative Analysis (discovering relationships in the data)
- Confirmation Analysis (visuals can help confirm our understanding and analysis of data)
Achieving graphical excellence is the goal of visualization. It requires accuracy and aesthetics and tells a story. To Tufte, it is “complex ideas communicated with clarity, precision, and efficiency. Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space.”
In writings on visualization, “the truth,” appears frequently. As communication professionals, we’re trying to tell stories that inform or persuade, like the example on the top is trying to get people to exercise more. There are facts in data, but the truth in visual storytelling is a complex proposition. Paolo Ciccarelli Head of Density Design explains, “The visual storyteller is fully responsible for the visualization, not data and its accuracy. A visual storyteller shouldn’t see himself as a holder of any truth. Phenomena are often complex and fuzzy, show many different dimensions, and can be perceived from many different points of view. A visual narration rarely can be scientifically accurate because, as with every type of narration, it deals with causality of events, and causes are often fuzzy.”
Yau uses a cooking analogy, “You are the chef and datasets, geometry, and color are your ingredients. A skilled chef, who knows the process of how to prepare and combine ingredients and plate the cooked food, is likely to prepare a delicious meal. Likewise, with visualization, when you know how to interpret data and how graphical elements fit and work together, the results often come out better than software defaults.”
I created the visual at the top, which tells the story about how sedentary American adults have become. I used data from the Centers for Disease Control and Prevention’s National Center for Health Statistics (NCHS). Rather than using a stale bar graph, I decided to incorporate a photograph to add visual interest. I was inspired by the work of artists like Sarah Illenberger, who uses photographs of everyday objects to illustrate data.
For my graphic, I used weight plates to represent the amount of exercise Americans get. I use a large weight plate to represent people who met both aerobic and muscle building guidelines. The medium-sized plate represents people who met one of the guidelines, and the small plate is for people who met neither guideline.
I used size and distance to tell the story. The size of the weight plates indicates success. I want the large plate to symbolize what we should strive for. I used distance to show our success rate—the higher the percentage, the farther from the plates. The contrast tells the story. The largest percentage (45%) of people who met neither guideline is farther from the smallest weight plate. Ideally, the percentages (or distance) would correspond with the size of weight plates so that the largest plate would have the highest percentage (i.e., more people meeting both guidelines) and longest line.
Data visualization is a burgeoning field and is only going to become more important as interactivity is introduced to visuals. Communication professionals should immerse themselves in the field, so they can select or create the graphically excellent visuals that tell their stories.
Data is beautiful: 10 of the best data visualization examples from history to today. Retrieved from https://www.tableau.com/learn/articles/best-beautiful-data-visualization-examples
Data visualization beginner’s guide: A definition, examples, and learning resources. Retrieved from https://www.tableau.com/learn/articles/data-visualization
Information visualization – A brief introduction. (2019). Retrieved from https://www.interaction-design.org/literature/article/information-visualization-a-brief-introduction
Klanten, R., Ehmann, S., & Schulze, F. (2011). Densitydesign. Visual storytelling: Inspiring a new visual language (1st ed., pp. 10-17) Gestalten.
Tufte, E. R. (1986). The visual display of quantitative information (2nd ed.). Cheshire, Connecticut: Graphics Press.
Yau, N. (2013). In Lowe J. (Ed.), Data points: Visualization that means something. Indianapolis, Indiana: John Wiley & Sons, Inc.