Info Vis Tufte Principals

What is graphical excellence?

Communicating interesting data with clarity, precision, and efficiency—showing many ideas in little space with little ink, while telling the truth.

What is graphical integrity?

Representing the data honestly, without visual choices that mislead the viewer.

What is the lie factor?

The size of the effect shown in the graphic divided by the size of the effect in the data.

What does a lie factor near 1 mean?

The visual effect is proportional to the effect in the data; a large difference from 1 suggests possible distortion.

What is data-ink?

The ink in a graphic used to display data information.

What is the data-ink ratio?

Data-ink divided by the total ink used in the graphic.

How can you maximize the data-ink ratio?

Use more of the graphic’s ink to show non-redundant data information; remove unnecessary decoration.

What is chartjunk?

Extraneous visual material that distracts from the data’s message.

Why show comparisons?

Comparisons help viewers see similarities, differences, and patterns in the data.

Why show causality?

When the data supports it, show relationships that help viewers understand what may cause an outcome.

What does “use multivariate data” mean?

Show multiple relevant variables together so viewers can understand their relationships.

What does “integrate text, images, and numbers” mean?

Bring these elements together so they support one another in explaining the data.

Why establish credibility?

Identify the author and data sources so viewers can judge where the information came from.

What does “focus on content” mean?

Prioritize the information and message over decoration.

Why should a chart have a baseline?

A baseline helps viewers judge values fairly; avoid truncating a scale in ways that distort differences.

Why use a consistent graphical scale?

Keep visual measurements—such as height, length, width, or volume—proportional to the values they represent.

Why give a chart context?

Provide enough surrounding time, geography, or other context to interpret the data fairly.