Alberto Cairo's Visualisation Wheel

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Alberto Cairo’s famous Visualisation Wheel, introduced in his book, The Functional Art, is a collection of twelve dimensions that help judge the trade-offs involved in the creation of data visualisations or infographics.

I find the original design, using arrows around a wheel, confusing, so I opted for a more conventional representation, in which the opposing dimensions are easier to grasp.

The trade-offs are as follows:

Abstraction vs Figuration

Abstraction Figuration
More conceptual: less strokes, less ink, etc. More ‘real life-like’ using pictures, icons, etc.

Example: A visualisation high in figuration may use icons of gold coins to represent one million dollars when describing celebrities’ salaries, so that a celebrity that earns three million dollars is shown next to three gold coins.

Functionality vs Decoration

Functionality Decoration
Only visuals that deal with the data itself. Artistic embellishments.

Example: A visualisation high in decoration, can show a stock’s valuation over a picture of a roller coaster.

Density vs Lightness

Density Lightness
As much detail as possible is provided. Only salient data is shown.

Example: A visualisation high in density may include 100 export industries that contribute to a country’s GBP, whereas one focused on lightness may either collapse the 100 industries into five broad categories, or bucket industries 6-100 into ‘Others’, focusing only on the top five.

Multidimensionality versus Unidimensionality

Multidimensionality Unidimensionality
Focus on covering as many dimensions as possible. Focus on the dimension that matters to the point the visualisation is trying to make.

Example: A visualisation high in multidimensionality, which describes a population’s income statistics, may cram into the same diagram, not only the income distribution, but the amount of it that goes into municipal and federal taxes, as the salary increases.

Originality vs Familiarity

Originality Familiarity
Most appropriate visualisation for the data at hand. Use of more traditional visualisation styles even if not the best fit for the data at hand.

Example: A visualisation high in originality may use a tree map to describe the differences in salary between various types of executives (CEO, CFO, CIO, etc.) and regular employees, as opposed to a simple bar chart.

Novelty vs Redundancy

Novelty Redundancy
Every data point is communicated only once. A salient point that the visualisation is trying to make may be shown using two or more approaches.

Example: A visualisation high in redundancy may highlight that the CEO is the top earner in a company, not only but displaying her salary with the tallest bar, but, by also highlighting the bar in red.