Data storytelling and storytelling with data: is there a difference? A fellow conference attendee posed this question to me during last month’s Tapestry Conference in Annapolis. After thinking for a moment, I responded that for me, the difference lay in the process.
I envision data storytelling as when you’re looking at data and want to know, “What is this data trying to tell me?” Storytelling with data for me is where you have a story in mind and seek data to substantiate it. Data storytelling feels more quantitative; I imagine needing to collect, clean, manipulate, and analyze the data before crafting the story. Storytelling with data, however, feels more fluid, with the story and the data coming together concurrently.
I acknowledge this may be complete bunk, and I welcome thoughts and critiques from others. At the end of the day, defining data storytelling may be less important than actually doing it. But after attending the second Tapestry Conference on data storytelling, I’m left itching for a framework, or at least continued conversation. Data storytelling is a beautiful concept, applicable across many domains: journalism, academia, technology development, business, advocacy, public policy. It’s also in its infancy, and defining it might force structure on a realm that needs exploration and freedom.
That doesn’t mean we should avoid descriptions of what constitutes good data storytelling. Journalist and infographics professor Alberto Cairo offered a starting point in his keynote (slides) on visualization for communication as “the insightful art.” Visualization for general audiences, he said, should be:
1. Truthful: Present your best understanding of the truth.
2. Functional: Choose perceptual elements (e.g., color, font) that help your audience understand what you want to convey.
3. Beautiful: Please the senses of your reader.
4. Insightful: Help your reader understand the main point; explain what is surprising, relevant, or interesting about the data.
5. Enlightening: Change someone’s mind for the better.
Personally, I would put “beautiful” last, not because it’s unimportant, but because for me, conveying information comprises the core of data storytelling.
Cairo encouraged us to be evidence-driven communicators, not activists. This is 100 percent true for journalists. However, activists who want to tell their story should feel welcome to adopt the principles of data storytelling. I agree that infographics should not massage data or mislead readers. But, as my aforementioned definition suggests, it’s possible for the story to precede the data.
Jock Mackinlay, researcher and Tableau Software VP, offered one check against misguided data storytelling: provide raw data with visualizations. Doing so can hook readers into your visualization, letting them explore it for themselves. It also validates the author and can promote conversation, enabling others to carry analysis further.
The importance of data literacy underpinned both presentations. Readers are going to see infographics from journalists and marketers, and they need to know how to differentiate them. Raw data provides the audience with a powerful tool, but only if the audience itself feels capable and empowered to take that data and run with it. Plenty of people do feel this way, and I hope that future Tapestry conferences will help us think of ways to build data literacy in our schools and workplaces so that even more people do.
Stay tuned for more Tapestry Conference posts.
4 thoughts on “Data Storytelling: A Definition?”
Francis Gagnon beautifully summarized the idea of a language for data storytelling here: http://www.chezvoila.com/blog/tapestry14