Everyone talks about big data. The real story is in the small data. Data is the new oil -- plentiful, but unrefined. It requires the discipline of analyzing, distilling and visualizing finding the story and turning it into actionable insights.
Here are three essential strategies for expressing yourself effectively with information graphics.
1. Data visualization is about telling a good story.
The question I often get is: What software should I use? Of course, all data visualizations are implemented with some sort of software. Let me be clear – that’s the final step and not the first. When I studied data visualization at Yale University under Edward Tufte, a pioneer in data visualization, we started with pencil sketches. We focused on concepts. That’s still the right approach.
Illustration from - The Wall Street Journal Guide to Information Graphics.
In any story, content comes first. The essential elements of good information graphics are:
“Rich content brings meaning to a graphic.
Inviting visualization interprets the content and highlights the essence of the information for the reader.
Sophisticated execution brings the content and the graphics to life.”
— excerpt from The Wall Street Journal Guide to Information Graphics.
2. An information graphic is not a form of self-expression. It always has a targeted audience.
From my days as a graphics editor at The New York Times and head of graphics at The Wall Street Journal, I learned my audience is the most important group of people in my work. Millions of readers means of having millions of critics on a daily basis. Understanding my audience helps shape my graphic. In fact, some graphics are literally a matter of life or death. For example, a lab report with clear illustrated graphics about blood pressure can motivate patients to exercise more and change their diet. However, if the graphics are overly complicated, the report is not only useless, but dangerous. We have to take the perspective of our audience and approach the graphic solution with conviction and empathy, as well as accuracy.
3. Color should be used to differentiate hierarchy of information.
Everyone can perceive the difference in shading, but they may not differentiate certain colors. “Color combinations such as red/green … can be similar in value or lightness. The lack of contrast in lightness makes it virtually unreadable for color-blind users.” — excerpt from The Wall Street Journal Guide to Information Graphics. And yet, we see these faulty color combinations all the time. The key is to develop a charting color palette with the least number of colors, but with multiple shades of the same hue. According to the National Institutes of Health, about 1 in 10 men have some form of colorblindness. Do you want your message to get lost?
Many professionals over-complicate the design and concept of data visualization. My philosophy of data visualization is straight forward: Know the content, distill the information and put my audience first.
The views expressed here are Wong’s own and do not necessarily represent those of the Federal Reserve Bank of New York.