Mercy on our minds: lightening cognitive load with the known-new contract

Lawrence Evalyn and I have an interdisciplinary friendship. I study research methods and data visualization; he studies eighteenth century literature and the digital humanities. I taught him about pivot tables; he taught me about sentence stress. I still think I got the better half of that exchange.

Sentence stress is my favorite tool for writing about complicated topics. Communicating complexity is also my goal in data visualization, so sentence stress is a natural complement to a conversation about data storytelling.

According to the concept of sentence stress, every sentence has two parts: the topic position and the stress position. A sentence’s stress position establishes a sentence’s main idea. It always comes just before a full stop. For example, “When the pirates come over, we played board games” emphasizes the board games. “At our board game night, we played with pirates” emphasizes the pirates.

Conversely, the topic position is the start of a sentence. The topic position links the sentence position to what the reader already knows. Topic and stress can interweave across several sentences to make a continuous chain of meaning. Take the following paragraph:

“My friend Anne recently joined a pirate crew. The crew sails Chesapeake bay to rob and pillage, which is pretty intimidating. When they’re not storming the high seas, though, they’re very friendly.

The topic positions link back to the stress position in the previous sentence. The link between topic and stress is also called the known-new contract. In the known-new contract, a sentence connects to what the reader already knows, then introduces a new piece of information. Following the known-new contract builds methodically towards a point, without losing the reader along the way.

Data visualization can also sign on to the known-new contract.  Hullman et al. studied a similar technique in sequencing narrative visualizations. Narrative visualization refers to a linear series of data visualizations, like a slideshow. The Hullman study suggests that narrative visualizations are most effective when only one aspect of the visualization changes at a time. A graph about pirate raids in the Chesapeake Bay in 2018 could transition to a graph about raids in the Chesapeake Bay in 2017, or a graph about raids in the Caribbean Ocean in 2018. Changing both the time and the location would make the narrative more difficult to follow. Like topic and stress positions in sentences, known information from the first graph supports the new information in the second graph.

The known-new contract may benefit visualizations because it reduces cognitive load. Readers and audiences can hold a limited amount of information in mind. Minimizing that load keeps the audience focused on content. Making just one change in a transition between graphs allows for easy comparisons; making two or more changes between charts may increase cognitive load so much that it’s difficult to draw meaningful connections.

In Better Presentations, Jon Schwabish suggests another one-change-at-a-time technique: layering. Rather than displaying a complicated visualization all at once, he suggests adding and discussing one component of the visualization at a time. Those simpler pieces ultimately layer to build the full, complex visualization. Breaking down the visualization lets the audience process manageable amounts of information while following a narrative. For a few examples of layering, see his blog post here.

The known-new contract also helps to directs attention. When writing about sentence stess, professor of rhetoric George D. Gopen says that readers focus on terms in the stress position. He writes, “Your reader doesn’t know what you think is important: they will assume that whatever is at the end of the sentence is your main point, and reverse-engineer an interpretation of the sentence around that assumption.”

Switch “sentence” with “graph,” and the same principle applies to narrative visualizations. If a narrative visualization starts with a complex graph, the audience will pick some their own focal points. Those focal points may or may not connect to the story at hand. Instead, a designer can intentionally direct audience attention through layering or single-change transitions. These techniques can deliver a story in digestible pieces, maintain a chain of meaning with minimal cognitive load, and communicate the designer’s priorities while preserving complexity.

The Hellman paper does note an interesting exception to single-change transitions: reverse sequences. Imagine a narrative visualization about pirate raids at various locations and times. A reverse sequence would have one transformation per transition:

  1. 2018, Chesapeake Bay
  2. 2017, Chesapeake Bay
  3. 2017, Caribbean
  4. 2018, Caribbean

Compare this to a parallel sequence:

  1. 2018, Chesapeake Bay
  2. 2017, Chesapeake Bay
  3. 2018, Caribbean
  4. 2017, Caribbean

The reverse sequence has one transition between each visualization, while the parallel sequence repeats the same year-to-year comparisons in two different contexts. The parallel sequence has two transformations between visualizations 2 and 3, while the reverse sequence has one transformation. But participants still remembered the parallel sequence more easily than the reverse sequence. Familiar comparisons (like the parallel sequence) may reduce cognitive load more than comparing familiar information.

The lessons of topic/stress positions adapt to mixed media scenarios, such as a presentation or a piece of data journalism. Data-driven stories don’t always go in straight lines: they are full of alleys, byways, and unexpected connections. But transitions in any medium are easier to follow when familiar context shepherds in new information.

A note: Speaking of narratives, I’m attending Tapestry at the University of Miami later this week—let me know if you’d like to say hi! And if you’re interested in gothic novels, Shakespeare, or the finest graphs about dueling, Lawrence can be found on Twitter at @LawrenceEvalyn or at his charming fortnightly newsletter.

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s