Georgia Institute of Technology faculty, scientists, GIS specialists, and graduate students launched a tool that provided real-time, localized information on the estimated risk of COVID-19 exposure by attending an event.
In talking with their team it was clear that their empathetic perspective of the audience and communication-focus helped successfully share their insights with event planners, policy makers, various news outlets and individuals – adding up to ultimately over 8 million unique users around the world.
Lessons learned from the GA Tech team about their experience building the COVID-19 Event Risk Assessment Planning Tool can apply to visualizations across many different industries and use cases – whether you are communicating to a handful of executives at your company or out to the world:
As a Shiny developer, make sure that you have a specific question in mind. What is the problem that you have that your app is helping them solve? Think about who your audience is going to be and what they would use this for. For the COVID-19 Event Risk Assessment Planning Tool, this question was “what is the risk level of attending an event, given the event size and location?”
View your audience through a lens of empathy. Think about metrics that people can really get a grip on and visualize. For example, the risk of attending a local event with 100 people in your own town vs. communicating this as cases per 100,000 people. If you want to communicate something that’s critical to the public, put it in the right terms.
Balance the straightforwardness of your visualization. You don’t have to anticipate every single question. With every feature or piece of information included, ask yourself if this supports your overall point? Importance of continued communication.
Keep the lines of communication open with your users. If you share a visualization, make sure that people have a clear way to contact you (email, Twitter, LinkedIn) with questions or feedback. Their team made an intentional effort to be available for local news particularly. They were responsive to the kinds of decisions people were making and adjusted the app to match their needs with event sizes for example.
Check out their Shiny application here.