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All visual cues should help your reader interpret your data.
Extra visual decoration will hurt your audience's ability to interpret the message of the visualization. This extra decoration is called "chart junk."
Salvaging the Pig
Example of how to minimize chart junk while emphasizing the information.
Exploratory vs. Explanatory: Is there a specific message you want to convey?
Interactive, dynamic, or static: Would you like the audience to manipulate or play with the information?
Think about medium: How will the audience receive/interact with the information?
Audience: Who are they and what do you want them to take away from your visualization?
Overview vs. Details: Do you want a big picture of your data or do you want to drill down into important details?
- Label axes and keys to make the visualization easier to understand
- Sources should always be included and easily findable
- However, remove any annotations or extra information that do not add to the reader's understanding!
Characteristics to Consider
- Show the data --> this may seem obvious but make sure that your data is front and center in your display and that any additions you make to your visualization do not cover up the purpose of showing the data
- Avoid misleading what the data represents
- Present quantitatively as much as you can in the space you have
- Make large data sets coherent; you do not necessarily need to include ever single data point but can rather be representative of a large data set
- Encourage the eye to compare different pieces of data
- When appropriate, reveal the data at several levels of detail, from a broad overview to the fine structure
- Serve a reasonably clear purpose: description, exploration, tabulation or decoration
From Edward Tufte's The Visual Display of Quantitative Information
Books about Data Visualization