Earlham Libraries Home: Data Visualization: Designing a Visualization

Chart Choosers

If you have collected and processed a data set but need some help with choosing an appropriate visualization type, you might find one of these "chart choosers" helpful.

It's useful to have an idea of what might be interesting about your data first, so that you can select a visualization type that will highlight that part of your data. If you're still exploring your data, you might want to try a broad range of charts and combinations.

Chart Chooser
Choosing a Good Chart
The Data Visualization Catalogue
This site presents a nice graphical summary of visualization types. For choosing a chart, you might want to "Search by Function", which will guide you to possible visualization types according to functions such as showing "Relationships", "Parts to a whole", "Distribution", "Flow", etc. Note that it shows possibilities, not necessarily which visualization types would be most highly recommended.

Designing a Data Visualization Project

Fry, B. (2008). Visualizing data. Sebastopol, CA: O’Reilly Media, Inc.
Seven Stages of Visualizing Data (p. 5): Acquire, Parse, Filter, Mine, Represent, Refine, Interact
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Acquire: Obtain the data.
Parse: Provide some structure for the data’s meaning, and order it into categories.
Filter: Remove all but the data of interest.
Mine: Apply methods from statistics or data mining as a way to discern patterns or place the data in mathematical context.
Represent: Choose a basic visual model, such as a bar graph, list, or tree.
Refine: Improve the basic representation to make it clearer and more visually engaging.
Interact: Add methods for manipulating the data or controlling what features are visible.
Planning and Designing Effective Data Visualizations
Has links to slides and notes from Noah Iliinsky.
Visual Encodings
If you have a general idea of the type of chart you'd like but don't know exactly how to use your data variables to make that chart, this "visual encodings" table might help. For example, it can help you know when to have colors represent values of a variable and when that might not be an appropriate encoding.
Eight Principles of Data Visualization
Graphs on Multiple Slides
The Squint Test

Infographics Design Resources

EARLHAM COLLEGE Infographic PAGE

Infographics are a popular way to tell a story using data, but it's often difficult to get started producing them yourself because they require a combination of storytelling, graphic design, and data visualization skills. There are also many possible tools you can use to produce them, from Adobe Illustrator or InDesign, to PowerPoint, to various online tools such as Canva or Piktochart. Below are a few resources you might find helpful to get started learning those skills and tools.

How to Design Infographics (Canva blog)
The Canva site has many very helpful posts. This one is a good place to start, but feel free to explore other articles in their Design School by clicking the LEARN link at the top of the page.
Canva tutorials
How to Make Powerful Infographics in PowerPoint (YouTube)
I don't particularly connect with Mike Parkinson's personality and style, but he gives a lot of great guidance, such as having a purpose, taking your audience into consideration, only telling a micro-story, sketching, and only rendering once you have the other work done. It's a good start for how to use PowerPoint graphics tools for creating infographics rather than a more expensive, powerful, and less accessible tool such as Adobe Illustrator.
Infographic layout cheat sheet (Piktochart)
Infographic design process (Piktochart)
On designing a custom visualization
On visual design

Guide Creator

Jose Ignacio Pareja

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Subjects: Biochemistry, Biology, Chemistry, Computer Science, Data Science, Economics, Environmental Sustainabilty, Geology, Mathematics, Neuroscience, Physics & Astronomy