Typefaces for Communicating Complex Information

Numerical information is commonplace in science. It appears in charts, tables, graphs, maps, and technical illustrations. Often, the visualizations that showcase these numbers get complex quickly, as they contain data points, axis labels, legends, titles, and notes. Even in non-scientific or consumer visualizations, numerical information can be tricky. Think of recipes, nutrition labels, menus, and box scores.

Displaying data so it can be consumed easily by readers is one of the most challenging aspects of graphic design. Choosing the right typeface for a set of numerical information needs to be driven by the nature of the data set itself, but it also needs to adhere to any guidelines established by a company’s brand style manual. Importantly, it also needs to be readable in multiple published formats. For example, it’s now common for data to appear in print, in PDFs read on screens, and in slide decks projected in large conference halls. Each of these display scenarios might call for a slightly different approach to handling typography.

In this blog, we will review key considerations when choosing typography for complex data sets. We will explain the difference between data, data visualizations, and infographics. We will present the general categories of type styles available, including specialized styles designed for complex data, and we will provide a set of guidelines for selecting typefaces that ensure your numerical information is accessible, readable, and understandable.

The Different Lives of Numbers

If you work for a science-based business, communicating data, in some capacity, will be necessary. You could be a materials scientist reporting data on your company’s latest innovation or a marketing specialist at a biotech firm communicating research results to potential investors. Regardless of your role, what you produce will likely fall into one of three categories — raw data, data visualization, or infographic. Let’s review each of these in more detail to understand how they differ and how typography choices impact readability and comprehension.

Data

Data in its raw form is defined by Merriam Webster as “factual information (such as measurements or statistics) used as a basis for reasoning, discussion, or calculation.” In everyday life, this looks like long lists of measured values, dates, times, coordinates, or other similar quantitative information, without much explanation or story explaining what it means. Often, such data is organized into tables, which brings some form and structure to the information, as shown below.

For tabular data, the choice of typeface can have a significant impact on how numbers display. For example, most standard typefaces feature proportional figures, meaning that the width of each number can vary. Also, in some character sets, certain numbers extend below the baseline, the line upon which most letters sit. The example below shows values taken from the same data set represented above, but with a different typeface. Notice how the odd numbers extend below the baseline, which creates some unevenness in the visual presentation of the data.

In monospaced typefaces, all characters take up the same amount of horizontal space. Other typefaces generally use proportional spacing, where characters use different amounts of horizontal space. These typefaces usually include an additional set of tabular figures, where each number takes up the same amount of space. Both of these options can be useful when typesetting tabular information because they make the data uniform and easier to process. See the example below.

Data Visualizations

A data visualization takes raw data and turns it into a graphical representation. Data visualizations can appear in many forms like graphs, diagrams, charts, plots, candlesticks, and waterfalls. Almost 60% of the population describes themselves as visual learners, so it’s not surprising that visualizations make it easier for people to understand how their data connects. Not only do people learn faster from data visualizations, but they also make faster decisions. The examples below show five different kinds of visualizations.

1. Column Chart

2. Bar Chart

3. Line Graph

4. Donut Chart

5. Bubble Plot

Each of these visualizations features a sans serif typeface, which is another critical decision when it comes to communicating complex data. Sans serif typefaces do not have the “tails” and “feet” — the short lines stemming from and at an angle to the upper and lower ends of the strokes of a letter — that serif typefaces do. Sans serif typefaces include Arial, Helvetica, Futura, Open Sans, Gotham, and Calibri. They offer a more modern and simplistic look, as they were developed during the Bauhaus art movement in Germany, which favored function and minimalism. Sans serif typefaces offer a clean and easy-to-read appearance that is helpful when used in digital texts and more technical texts.

Most data visualizations have several typographical elements, each of which must be considered carefully. Study the example below, and you’ll see these elements: (1) Title, (2) Y-axis, (3) Legend, (4) Data, (5) X-axis, (6) Footnote, and (7) Notes.

In this example, the same typeface, in different weights, is used for all elements of the visualization. It is also possible to use different typefaces for various parts of the graphic. Some designers will use a serif typeface for the title, axis labels, and notes, while they will adopt a sans serif for all remaining elements. Often, these decisions are influenced by the general design approach taken in a larger context. For example, most visualizations appear in a longer narrative (a paper or publication), with specific character and paragraph styles chosen for headlines, subheads, and body copy. These same styles can be applied to the visualizations used to support the narrative.

Footnotes (element #6 in the example) provide evidence of a larger set of specialized characters that can help convey additional meaning to the audience, and most typefaces will offer a robust family of these characters for use with data. These include:

• Subscripts and superscripts are smaller characters placed above or below the text line to convey an additional layer of meaning. Subscripts fall below the text line and are often used in chemistry, math, and physics (e.g., H₂O and m₁v₁ = m₂v₂). Superscripts are more common and fall above the text line. In addition to footnotes, they are most commonly used in ordinal numbers (1^st, 2^nd, 3^rd, etc.), trademarks (Nexium^®), mathematical formulas (E = mc²), and other scientific notations, such as for isotopes (¹H, ²H, ³H, etc.).
  
  
• Reference marks and symbols are used to make keys and to sort information in general. Common symbols are daggers († and ‡) and asterisks (* and **), which can be used to mark footnotes as an alternative to superscript numbers. Another common symbol is the number symbol (#), which has emerged in the social media era as an indicator of a category or a classification. Section signs (§) and pilcrow signs (¶) are less commonly used in typesetting, but they sometimes make an appearance.

Infographics

Infographics have emerged as important storytelling tools in digital-dominated marketing. They bring together imagery, data visualizations, and narrative text to provide an easy-to-understand overview of a topic. Infographics often explain a topic in a linear, top-down manner and might end with a call to action. They capture readers’ attention with bold colors, typefaces, fonts, and images, but they also clearly lay out information in such a way that readers can more easily consume a complex story told through numbers, words, and graphics. The example below illustrates this clearly.

Designing an infographic requires attention to balance and hierarchy. Visualizations often feature a number of details, so they must remain large enough to make all of those details accessible. At the same time, the finished infographic can’t expand indefinitely because presenting it will be challenging. Defining a clear hierarchy of information, using typeset headlines and subheads, can be helpful with this by leading a reader’s eyes across or down the content as needed. We covered this extensively in How to Write Killer Headlines.

Display and decorative typefaces can also be helpful. These eye-catching and bold typefaces are meant to grab the reader’s attention, which is why they are used almost exclusively for titles and headers. Because they have a unique aesthetic, often with dramatic flourishes, decorative typefaces used in infographics can contribute significantly to a brand’s image. Consider the infographic below, which features a display typeface with strong serifs to showcase the title. Also note the introduction of all-caps to help elevate and emphasize the deck copy. All-caps should be used sparingly — a good rule of thumb for centered text, as well. Centered text can be more challenging to digest because it’s harder for a reader’s eye to track along the inconsistent left and right edges of type.

Selecting Type for Complex Data: Five Guidelines

1. Select typefaces aligned with your data set and purpose.

What kind of data are you working with? Do you have lots of tabular data? A long list of names, addresses, and phone numbers might be handled differently than a year’s worth of temperature, barometric pressure, and wind speed readings. Are you creating an infographic made with several detailed visualizations or an infographic with no numeric information at all (see below for an example of this). Make sure that your typeface matches your tone and doesn’t distract from the story your data should tell.

2. Don’t make typographic decisions at the last minute.

Typefaces immediately set the tone for your audience, so it’s important to think about them before you start moving pixels around. Also, something you might not realize — typesetting takes a lot of time. It’s painstaking work that requires many instances of selecting text and applying styles. If you change your mind about typefaces as you’re nearing completion of a graphic, you could lose a couple of hours making the updates.

As we’ve discussed earlier, thinking about the larger context for a graphic will help you make typography decisions. In the example below, a white paper, the body copy is set in Helvetica, which follows the brand guidelines (see #3 below), so a distinctive serif typeface was chosen for the accompanying graphics. This type pairing exercise was completed early in the project, then applied to all graphics throughout the paper.

3. Know your brand guidelines — and when to break them.

Brand guidelines provide clear direction to ensure the work product of all designers and creators has a consistent look and feel. At the same time, you don’t need to follow every single guideline to the letter, especially if they are making content mundane or difficult to understand. The tabular data below is a great example. The brand guidelines for this chemical company don’t specify the use of Helvetica, but the application of the clean, classic sans serif made the complex performance data much easier to read and consume.

4. Think about accessibility.

Various federal and state laws require that organizations make their web content and other electronic information resources accessible to individuals with disabilities. In addition to these laws, there are internationally recognized guidelines, launched by the World Wide Web Consortium (W3C) in 2008, known as the Web Content Accessibility Guidelines (WCAG). WCAG gives companies an actionable guide and resource for making a website accessible to users with disabilities.

All of these standards and guidelines ensure people with disabilities can access and understand online content. They offer very specific guidance around content attributes, such as:

• Color contrast
• Text size
• Text alignment
• Line spacing
• Line breaks
• Use of hyphenation

Bottom line: some typefaces, fonts, or color choices can be difficult or confusing to follow for people with reading or learning difficulties. A good rule of thumb is to always be mindful when choosing and formatting typography so that your finished work is as inclusive as possible. The timeline below was designed with accessibility guidelines in mind, ensuring high contrast and clear legibility with a clean, easy-to-read sans serif with several weights and styles.

5. Make good choices, even if they seem to fly in the face of conventional wisdom.

There are hundreds of decisions to make when typesetting complex data, and sometimes you must break rules for the sake of clarity and understanding. Consider these choices:

• Wide vs. Condensed
  It’s generally known that condensed typefaces will allow you to fit a great deal of text into a smaller space. Condensed type, however, can be challenging to read as letter forms shrink in size. Sometimes, a wider typeface set smaller can still accommodate large quantities of text, yet maintain legibility.
  
  
• Serif vs. Sans Serif
  We covered this several times, but that’s because it’s important. The serif vs. sans serif decision is fundamental to any design strategy. As we’ve mentioned, sans serif typefaces are popular in scientific settings because of the less-is-more tone they establish. It’s no surprise that almost every example in this article features a sans serif typeface. Sometimes, though, a serif typeface can be a useful alternative. Look at the example below, which is a simple infographic composed almost entirely of text. Here, the serif typeface provides a satisfying foil to the sans serif type used throughout the rest of this published report. Also, the serifs improve readability by “handing off” visual tracking from one letter to the next.

• Bold vs. Italic
  Both bold and italic styles have a similar effect — they draw the eye to certain text that’s either specialized (such as a book title) or important (such as a call to action). However, they send very different messages. Italic type was created early on in handwriting history to highlight text, giving it a sense of personal intonation. Italics are meant to show change in tone or nuance to a subject. Bold text emphasizes short phrases or headlines to increase their stopping power and memorability. Readers may interpret bold type as shouting, so it should be used sparingly to avoid overwhelming the surrounding content.
  
  
• Uppercase Type
  There are three main types of capitalization typically used in titles and headers: title case, sentence case, and all-caps. Title case refers to capitalizing every word except conjunctions and prepositions in a title, while sentence case refers to capitalizing only the first word and proper nouns. Title case is more often used in the arts (movie, book, and song titles). In contrast, sentence case is more often used in journalism or more scientific titles.
  
  In all-caps text, every letter is capitalized, though this style should be used judiciously because it can be difficult to read. No matter which capitalization rules you apply, do so consistently so readers can understand the hierarchy you’re trying to establish. The example below, taken from an infographic shows how various types of capitalization can be used together in a single design to help differentiate types of content.

• Color
  Color — both of type itself and of the background behind letterforms — plays a big role in readability. It is important to use high-contrast colors, especially digitally, so everyone is able to read your text easily. Black and charcoal gray are the most commonly used against a white background, while blue can prove to be difficult for some parts of the population to read.
  
  Reversed type refers to lighter-colored text set on a darker background, a treatment that can help emphasize important content. When white text is set on a black background, the text is said to be “knocked out” because, in the print world, the color of the paper appears through the letterforms. Like all-caps, knocked-out type should be used sparingly to ensure readability. The graphic below, which benefits from having a minimal amount of content, uses reverse and knocked-out type effectively.