With that in mind, here are some things researchers and designers at the Center consider when using small multiples to communicate our findings:Titles and labels: Our information graphics usually include a title that highlights a finding, with a subheadline describing what was measured or what survey question was asked..Small multiples contain many possible takeaways, and titles clarify for the reader which ones we’re most trying to communicate..Without titles to guide them, readers might still take away something from a particular display, but it might not be something accurate or meaningful.Common style, scales and references: A common scale and visual style help readers make accurate comparisons across panels, so we typically use the same color, type style and axis ranges — in other words, a template..Ideally, the only thing that should change is the data.Common reference lines can also help to make panels more easily comparable..In the example below, the designer included a gray line showing national public opinion on same-sex marriage to help contextualize the regional data being shown in each panel:Panel order: Ordering the panels by some value is another way to help readers wade through small multiples..It’s not always essential; in the example above, for instance, the panels are not obviously ordered by some value.But an ordered display can make findings more noticeable..For example, you could order the panels above from lowest to highest support for same-sex marriage in 2014, which would make it easy to identify the South Central and New England regions as the areas with the least and most support for same-sex marriage, respectively.Ordering panels by some value often results in a repeating pattern that changes slightly from panel to panel, almost like an animation..In this way, panel order helps give the reader a narrative to follow — a beginning, middle and end..Indeed, time-based small multiples can be ordered left to right in sequence, as in this example:Scale and pattern: The miniaturized nature of small multiples can sometimes mute differences between individual data points, making findings described in the title hard to see..Sometimes, small design tweaks can resolve this..Consider our earlier example graphic showing public opinion in eight Western European countries..A draft version used dots as data markers instead of horizontal strips, but that turned out not to be the best approach.. More details