_AH4501: International Health - Final Project Tool Box

Infographics (or information graphics) tell a story about a topic using one or several data visualizations with other visual complements. Infographics can include text, graphs, charts, diagrams, tables, maps, lists, and other forms of data visualization. The goals of infographics are varied, with some intended to provide information, others intended to persuade or call the audience to action. 

Data Visualization is the visual display of quantitative information. A good data visualization will make it easy for the viewer to interpret complex information, notice patterns in data, and identify key takeaways. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.

(Borrowed from Purdue OWL)

When you work with visuals containing data in your own work, such as charts, graphs, or images, how do you approach the display of those visuals? How does the venue in which you share, display, or publish your work shape the visuals? What are the best practices for assuring your visuals or data are displayed in the most accessible manner for your readers?

This resource covers tips and theories such as data visualization best practices for general visuals, using color appropriately for your chosen venue of display, and tips for ethical data representation. A slideshow with example images, in addition to a data visualization assessment handout, are included to help you revise your data visualizations to best approach your readers.

Determining the Best Information Type

When using programs like Microsoft Word, PowerPoint, MatLab, or similar programs that can help you generate visuals, it might be tempting to use flashy 3D or animated charts or tables. Readers can struggle to interpret data when the presentation type of complex, moving, or novel.

However, simplistic presentations of data and information are the often best when approaching universal readers. Consider these questions when deciding what type of information you are working with and how you might present it:

• Who are my readers? Will a specific visual presentation tool appeal to them more than other audiences?
• Where will my information or data appear? Will it be read in print, on screen, or seen in a slideshow presentation at a conference? How can the visual best appeal to my audience in this specific setting?
• What is the simplest method for displaying this data? Will a line graph represent my information better than a graph? What attribute of the information do I want to highlight most?

Additional questions to consider when choosing presentation types might include:

• What changes need to be made from displaying visuals from print to screen?
• How can you use the presentation types listed above to best communicate data to readers in a large lecture hall, conference room, or remotely?

Three E’s of Displaying Data

Visual scholar Edward Tufte details many categories of data display best practices in his book Envisioning Information, which offers a starting point for considering how to best display data. These concepts are references and extended here as the 3 E’s of Data Display and are further detailed in the slides below:

• Effectively: Assure readers can easily find your data alongside any text or verbal cues that refer to it. Take care to reinforce your written text or content with your data visualizations; do not replace or repeat information that could be best explained in a visual.
• Ethically: Always be honest with your readers with your visual data. Avoid inflating trends, data points, results, or scale with visual tools.
• Efficiently: Depending on where your data is being displayed, use color judiciously. Also assure that you utilize white space and page layout efficiently.

Considering Color & Contrast: Best Practices

Though other resources on the OWL explore color theory in more depth, this resource focuses on best practices for using color and principles of contrast for data visualizations.

When readers look at data visualizations, they expect to be able to interpret complex data quickly and easily. Using color or contrast well can provide an appealing reading experience for your audience, shaping the reader’s perception and understanding of your data overall.

Fonts, Layout, and Publication Guidelines

Your data visualizations will likely be presented alongside text, or work in concert with text such as titles, subtitles or labels.

When working with these elements, the following tips provide general approaches for assuring readers can easily access, read, and interpret the information you provide in your data visualizations. Other OWL resources on document design, layout, and typography provide more information on specific font best practices, document layout procedures, and persuasive design tactics.