Choose Tools to Tell Your Data Story
Editor’s Note: Data visualization is a powerful method for representing data, but with the wealth of data visualization tools available, getting started on the process can be a daunting task. As foremost experts in data visualization, Jack Dougherty and Ilya Ilyankou review the methodology behind choosing the best tools to tell a data story. We’d love to hear from you about what you think about this piece.
Do you feel overwhelmed by the enormous range of data visualization tools? There’s been so many different tools released in recent years that anyone would have a hard time deciding which ones to use. Even if you limit your choices to a dozen or so tools, how do you make wise decisions?
• Draw and Write Your Data Story reminds us to start with the most important item in your toolkit: your story. Begin by drawing pictures and writing questions or sentences to capture your ideas on paper, and then choose the most appropriate tools to create your vision.
• Ask Questions When Choosing Tools lists several criteria to consider when making software decisions. Many of us look for free or affordable tools in the perfect sweet spot — easy-to-learn, yet powerful.
Draw and Write Your Data Story
Before you dive deeply into software, think about the most important item in your toolkit: your story. The primary reason we’re designing visualizations is to improve how we communicate our data story to other people, so let’s begin there.
Push away the computer and pick up some old-school tools:
• colored markers or pencils
• lots of blank paper
• your imagination
First, at the top of the page, write down your data story.
• Is it in the form of a question? If so, figure out how to pose the question.
• Or maybe it’s in the form of an answer to that question? If so, spell out your clearest statement.
• If you’re lucky, perhaps you already can envision a full story, with a beginning, middle, and end.
• Whatever form it takes in your head, write out the words that come to mind.
Further down the page (or on a separate sheet), draw quick pictures of the visualizations that comes to your mind, even if you don’t yet have any data. No artistic skills are required. Just use your imagination.
— Do you envision some type of chart? Sketch a picture.
— Or do you imagine some type of map? Show what it might look like.
— Will your visualization be interactive? Insert arrows, buttons, whatever.
Finally, share your data story with someone else and talk through your preliminary ideas. Does your sketch and sentences help to convey the broader idea that you’re trying to communicate? If so, this is one good sign that your data story is worth pursuing.
Ask Questions When Choosing Tools
When each of us decides which digital tools best fit our needs, we often face trade-offs. On one hand, many of us prefer easy-to-learn tools, especially those with a drag-and-drop interface, but they often force us to settle for limited options. On the other hand, we also favor powerful tools that allow us to control and customize our work, yet most of these require higher-level coding skills. The goal is to find the best of both worlds: that “sweet spot” where tools are both friendly and flexible.
Before testing out new tools, try listing the criteria that guide your decision making process. What are the most important factors that influence whether or not you add another item to your digital toolkit? Here’s the list that came to our minds:
1. Price: Is the tool free, or is there a “freemium” model to pay for more features or higher usage?
2. Easy-to-learn: Is the tool relatively simple for new users without coding skills?
3. Power: Does the tool support large amounts of data, and various types of visualizations?
4. Customization: Can I modify details about how my work appears?
5. Data Migration: Can I easily move my data in and out, in case I switch to a different tool? Hint for historians: Future-proof your digital history projects! Choose tools that allow you to easily export and migrate data to other platforms. Design projects to keep your data separate from its digital presentation.
6. Hosting: Can I decide exactly where my data and visualizations will be stored online?
7. Support: Is the tool actively maintained by its creators, and do they answer questions?
8. Open Source: Is the tool’s software visible, can it be modified, and redistributed?
9. Security: Is the tool and my data protected from malicious hackers and malware?
10. Collaborative: Does the tool allow several people to work together on one shared product?
11. Privacy: Under the terms of service, is my data and work private or public?
12. Error-friendly: When something fails, does the tool point out possible problems and solutions?
13. Cross-platform: Does this tool work across different computer operating systems?
14. Mobile-friendly: Will it correctly display my work on various mobile devices and browsers?
That’s a long list! But don’t let it overwhelm you. Remember the two most important criteria for the many free tools that are currently available: easy-to-learn and powerful features.
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Jack Dougherty is a Professor of Educational Studies at Trinity College in Hartford, Connecticut. Professor Dougherty has taught data visualization to undergraduates at Trinity College and to thousands of participants in a global online course. He and his students have partnered with dozens of non-profit organizations, journalists, and researchers to help tell their data stories on the web. Ilya Ilyankou is an Independent Technologist. Ilya has been working with CTData Collaborative to build data visualization and data exploration tools for Connecticut for two years.
