Working With Visual Cues#
The wide range of customization or styling options when building a visualization can be overwhelming. We can think of these style elements as visual cues that can help a visualization achieve a desired communication or rhetorical goal.
Image source: Peter Aldhous, “Data visualization: basic principles”, Intro Data Viz (Fall 2016)
Common visual cues:
Length
Slope
Color hue
Volume
Angle
Area
Color intensity
To have meaningful visual cues, make sure the math adds up. That is, make sure you know what arithemtic operations are happening in the process of generating the visualization. One component of making sure the math adds up is knowing how the chart type you have chosen interacts with the underlying data. Another component, particularly for more complex statistical visualizations, is to make sure the visualization is communicating what you intend.
A great place to start for making sure the math adds up is Carl Bregstrom and Jevin West’s Calling Bullshit: Data Reasoning in a Digital World open curriculum and book.
The open curriculum covers topics like causality, statistical traps, sample size, correlation, and selection bias in relation to data analysis and visualization.
Their book Calling Bullshit: The Art of Skepticism in a Data-Driven World (Penguin Random House, 2020) is also a useful resource.
Meaningful visual cues are also true to the ‘feel’ of the data. This requires knowing enough about the underlying dataset to know when a visualization is not accurately representing the underlying data.
Design Workflows#
One overarching principle to keep in mind is that data visualization is an act of communication, and visual representation of information is inherently a form of storytelling. Spending time thinking abstractly or conceptually about what a data visualization needs to accomplish or communicate is immensely valuable. There are a range of words or terms that can describe this activity, including storyboarding or sketching.
A wonderful place to start is the work of data artist Giorgia Lupi.
Data Humanism, The Revolution will be Visualized PrintMag (30 January 2017)
Dear Data (Princeton Architectural Press, 2016)
Observe, Collect, Draw!: A Visual Journal (Princeton Architectural Press, 2018)
In April 2019, data visualization designer and artist Nadieh Bremer in collaboration with Google Trends released a “Why do cats * dogs …?” project featuring interactive visualizations exploring the how and why behind common pet-related Google search questions.
Bremer wrote a detailed blog post about the design process for the project.
“The Design Process of ‘Why Do Cats & Dogs …?’ personal blog (11 April 2019)
Another wonderful resource is data artist and former Library of Congress Innovator-In-Residence Jer Thorp’s book Living in Data: A Citizen’s Guide to a Better Information Future (Macmillan, 2020).
These resources are a useful starting place to explore strategies and practices for designing rich, meaningful data visualizations.