Textbook of Usability

Small multiples are a visualisation pattern in which a series of similar charts, each showing a different slice of the data, are arranged in a grid for direct comparison. The term was popularised by Edward Tufte, who advocated small multiples as a powerful alternative to complex multi-series charts.

Rather than overlaying 12 lines on a single chart (cluttered, difficult to compare), a small multiples approach displays 12 identically scaled panels, each showing one series. The viewer's visual system can scan across panels to detect differences and similarities — a task well suited to the parallel processing capabilities described in Chapter 2.

Key requirements for effective small multiples:

• Identical scales across all panels (so comparisons are valid)
• Identical encoding (same axes, same colours, same chart type)
• Clear labelling so each panel is immediately identifiable
• Sufficient size so each panel is readable
• Logical ordering (chronological, alphabetical, by magnitude)

Small multiples exploit the viewer's ability to compare adjacent, identically formatted charts. They work because the visual system can rapidly align features across visually similar panels, detecting departures from the pattern.

Common applications:

• Monthly infection rates across hospital wards
• Sales trends across product categories
• Weather patterns across cities
• A/B test results across user segments

Small multiples trade screen real estate for clarity — a worthwhile exchange when the goal is comparison across categories.