Creating Effective Visualizations

Your students have analyzed data and are preparing a presentation on findings and trends to communicate with their audience. Using effective visualization to communicate this information is important. To generate an effective visualization, ask your students to think through the following questions.

What story does the data tell?

When you use a visual representation of data, you are, in a way, telling a story and suggesting conclusions based on the data. It is important that this conclusion be clear, relevant to the question you are trying to answer, and valid. Be careful of trying to do too much with one visualization. Superfluous information or graphics can be confusing or even misleading. Even something as seemingly trivial as color choice may suggest unintentional and invalid conclusions (e.g. some colors, used together, may suggest contrast or an evaluation as good or bad). The later examples will elaborate on these guidelines further.

What type of visualization will best tell that story?

With all the visualization possibilities, it is important to think critically about the kind of visualization that will best suit the data and the conclusions. An example of a visualization that is often misused is a pie chart. When comparing relative amounts using percentages, a pie chart may be a useful visualization, but not in every case. If the values you are comparing are close enough, for example, a pie chart may not highlight any differences among them, as it is difficult for people to really tell the difference between, say, a 35% wedge and a 40% wedge. Another common misuse of pie charts (or other similar visualization methods) is when percentages overlap. A pie chart, by nature, is meant to represent non-overlapping percentages in order to gauge relative differences between disjoint amounts. Therefore, the percentages included should always add up to 100%.

Is the visualization clear? Can others draw clear and legitimate conclusions from it?

A good visualization is one that clearly presents the data in a way that is readable and understandable by someone who does not have the same background knowledge. Examine your visualizations critically, thinking from the perspective of someone with limited knowledge of all the work you have done. It is a good idea to ask someone to explain the conclusions they draw from your chart. If they are coming up with (invalid) conclusions you did not intend or missing the important points you are trying to present, then rethink the visualization strategy. Sometimes people may draw conclusions based on aspects of the presentation that you never considered and perhaps chose rather trivially, such as color schemes.

Know your audience. If you expect your audience to be aware of the data you gathered, the visualization may be different than if your audience has no access to the raw data.

A good visualization will catch the audience’s attention and focus it on the right things and not on the wrong things. Avoid distracting backgrounds and color schemes that detract from the important aspects of the data. Avoid cluttering up the visualization, which can confuse your purpose and make your conclusions hard to decipher.

Most people, especially students, have to do a presentation at some point in their life, and often those presentations include visuals. Garr Reynolds is a best-selling author and speaker, and his website here provides good advice about producing good slide shows.