I don’t know about you, but when something piques my interest — TV tropes, color theory, the life-changing magic of tidying up, anything — I have to wrap my mind around the “shape” of the related knowledge. I get sucked into reading (or listening to) whatever I can about the topic while under this spell.
A while back, I discovered that information design was its own field, and I wanted to know the fundamental principles and best practices. I also found myself lost. Whether it was picking out a learning resource, charting tool, or styling option, it wasn’t always clear why to choose one over the other. Like so many just starting out in the field, it was frustrating to hear the same answer to many questions: “It kind of depends.”
But are there certain sorts of problems that data visualization can help with or needs it’s especially good at meeting? In a recent conversation, we asked members of the Data Visualization Society (DVS) to give their take. Welcome to a rough guide on knowing where data visualization can help you.
1. To challenge assumptions and expand the mind
When a Swedish professor was taken aback by how much misconception existed in the world, he went on to make it a mission to “fight devastating ignorance with a fact-based worldview that everyone can understand”. His name was Hans Rosling, co-founder of Gapminder Foundation, and his common tool of choice? Charts on global trends, combined with great storytelling.
Data visualization is particularly good at helping us to think beyond our own personal experiences, especially if it’s on issues that are little known or not often covered in the media. When an event or issue easily springs to mind, we tend to exaggerate the importance or frequency of it. Likewise, we tend to downplay things that we are not as familiar with.
By making the data more memorable and “sticky” in our mind, vizzes can help overcome availability bias, which is our tendency to give preference to information or events that are more recent or observed personally.
The effect is amplified when we insert the audience in the data visualization. For example, in The New York Times’ interactive article ‘How Much Hotter Is Your Hometown Than When You Were Born?’ piece on climate change, the audience is asked to enter their hometown and year of birth. The article then goes on to compare the number of hot days one can expect today relative to when they were born, as well as what they can expect as they age. Climate change becomes something more personal and relatable.
That said, sometimes it takes more to convince your audience. In one dataviz practitioner’s experience, when the charts don’t match expectations, the audience’s first instinct may be to find fault with the data. Cultivating trust is necessary, particularly when audience members see themselves as domain experts on the topic.
2. To reason about data
It’s a myth that designing visualizations is only for the end of the data analysis process or when you are ready to communicate some insights. Coming up with quick and dirty prototype charts or even sketches has its benefits at the early stages.
The more obvious upside is that it’s easier to pick out patterns and outliers from a chart than chunks of raw data or rows of summary statistics. But besides using data visualization as a way to understand, we can also use it as a way to think. By translating our internal thinking process into objects in the external world, we clarify our ideas and make them more actionable.
In my case, thinking or prototyping through vizzes gets me in an experimental mode. It opens up more possibilities and curbs any pesky perfectionist tendency to get everything right the first time. For others, it can serve as a complementary approach to writing, which fosters a more sequential frame of thinking.
3. To unleash beauty into the world
Some pleasures cut across age, gender, and ethnicity: rainbows, bubbles, and ice cream to mention a few. When a data visualization looks and feels a certain way, it can give rise to similar feelings of delight.
Maybe we can’t always put a finger on the particular aesthetics that made the data sing, but we can usually agree that the visualization was beautiful. In this sense, the desire to produce a data visualization (or even data art) is linked to a human impulse to create beauty.
Some DVS members even see data visualization as a way of reclaiming space — to breathe new life into the serious spaces that typically neglect or reject beauty. Beauty embedded in a data visualization also has a functional role. To quote design guru Paul Rand:
Ideally, beauty and utility are mutually generative. In the past, rarely was beauty an end in itself… The function of the exterior decoration of the great Gothic cathedrals was to invite entry; the rose windows inside provided the spiritual mood.
In the data visualization context, beautiful design serves to guide users to key elements and aids in their understanding. Yet, despite the net positive results, people often resist the pursuit of beauty or dismiss it as a frivolous act altogether, particularly in the business world. When handling dashboard designs, dataviz practitioner Jason Forrest previously found his colleagues rejecting suggestions of beautiful designs in favor of something more basic. His workaround was to make the design prototype anyway, which got people more interested in the suggestions.
4. To connect in an attention-starved world
Data visualizations, particularly beautiful ones, have the benefit of acting like eye candy. They can get your audience to stop, look, and hopefully, engage with the data. Information designer and LinkedIn instructor Bill Shander tells us not to underestimate the “value of eye candy to simply generate interest”.
The Pudding is a great example of tapping into data visualization’s eye candy power with its rich visual essays on topics like how women’s pockets are inferior and the laughter climax of Ali Wong’s stand-up comedy. As data journalism becomes a global field, we will see more outlets drawing on data visualizations to create compelling content.
Why does it work? As a visual metaphor for data points, data visualization has the ability to make ideas more easily digestible and captivating at the same time. In this way, ideas embedded in visualizations are more likely to persist and spread.
It’s not only dataviz or data journalism folks who recognize this, either. Marketers know that eye-catching data visualizations combined with a powerful narrative can be very shareable and persuasive, as exemplified in the “Data Visualization + Data Storytelling Is Marketing Gold” article making the rounds on the internet.
5. To define and shape data culture
If the hallmarks of a culture include the community’s shared languages, food, music, and social habits, then in much the same way, data visualization practices are a hallmark of an organization’s data culture. Ultimately, the kind of data visualizations that can be produced is the result of how data is organized and integrated from various sources in the organization.
As DVS founding member Elijah Meeks puts it, “Do you boil everything down to a few KPIs? Are you comfortable with sophisticated representation? Do you think about uncertainty? All that is expressed in the data visualization that you use in your presentations, your email reports, and your public dashboards.”
And despite the growing imperative to be data-first, data-driven, or [insert new buzzword] in today’s economy, it’s not possible to build competency in everything at once. Data visualization can be a gateway for getting people to be more comfortable with unfamiliar data practices. For dataviz practitioner Wendy Small, the use of more simple data visualizations like line charts has been a healthy and effective way to encourage new approaches to reading data as part of a data literacy initiative.
The clarity that data visualization provides also encourages people to work better. When dataviz practitioners Keisha and Evelyn Münster handled projects on process-related data, they found that visualizing the process details proved more illuminating than relying on some aggregated numbers. It also sparked better conversations about what was going on.
6. To experience hobbies (or anything else) through a different lens
Data visualization is not all serious business. It lets us geek out to our heart’s content on our interests. Exploring the visual patterns that emerge from a data set on a hobby is another way to enjoy the hobby.
If you enjoy beer, check out Nathan Yau’s chart of beer styles, which looks like a beer-colored mosaic, complete with details on flavor as well as how high each beer style tends to be in alcohol content and bitterness. It’s a great way to explore multiple types of beer, from the American Lager to Fruit Lambic, without the risk of a hangover. Or maybe you are a fan of meta, and you may enjoy Christian Swinehart’s data storytelling of the storytelling structure in Choose Your Own Adventure Books. There seems to be something out there for everyone.
What about the “quantified self” movement, where people mine vast collections of personal data and visualize them?
When journalist Lam Thuy Vo’s marriage dissolved a number of years back, she created a blog Quantified Breakup to organize her responses in data visualizations. One post showed her apartment-related weight loss as she got rid of furniture. In another post, she tracked text messages exchanged with people she met online after the divorce and visualized those messages as sparks that flew off the screen.
It’s like taking pictures to remember a beach vacation in Bali, except we’re not just logging one-off moments. We’re tracking the same thing over time and compressing the result into a series of ebbs and flows or whatever patterns it shows. In some way, the process of visualizing this data functions as a form of self-discovery or, if we’re hurting, self-healing.
A Final Note
There you have it, six reasons we create data visualization. This list is not exhaustive by any means, but it shows the value of data visualization as it sits at the intersection of beauty, influence, and expression.
Thanks to the Data Visualization Society members for contributing to the discussion, including: Alexwein, Bill Shander, Bridget, Cameron Yick, Elijah Meeks, Evelyn Münster, Erica Gunn, Jack Merlin Bruce, Jason Forrest, Keisha, Matthew Montesano, Nicole Edmunds, Stephen Singer, Wendy Small.