Representing data visually so that others can understand requires interdisciplinary problem solving and creativity. Sometimes beautiful design does not tell the full story, or the significance of data is undermined by the way it is presented. It’s that happy medium—strong design that maximizes a user’s understanding of data—that the 60 students enrolled in the spring semester’s three-week Collaborative Design course chased after.
Mimicking the inherently collaborative nature of project teams in the working world, students majoring in data analytics, computer science and design worked side by side to create data visualizations representing issues in education, public health, economics, gentrification, demographics, geology, transportation and urban structure. Design Assistant Professor Yvette Shen and TDAI affiliate and Computer Science and Engineering Professor Han-Wei Shen co-taught the popular inaugural course.
The results? Eleven dynamic projects that were unveiled during an April 30 presentation attended by students as well as other members of the Ohio State community. Using available data from resources such as school districts, Centers for Disease Control and Prevention and the U.S. Census Bureau, teams worked together to create visualizations illustrating complex challenges impacting central Ohio neighborhoods and residents. They came up with problem statements and let the data provide the evidence that bolstered—and in some cases, disproved—their assumptions.
Using interactive scatterplots, maps, bar graphs, pie charts and more, teams explored topics such as school district performance, the geographic distribution of the city’s HIV resources, Ohio’s life expectancy rates and why so many companies choose Columbus as a place to test new products (spoiler alert: using demographic data, the team couldn’t pinpoint the reason). Some projects addressed concerns that hit home with students, like how Columbus’s Old North neighborhood stacks up against nearby Clintonville in terms of affordability and safety.
The teams’ findings have a greater use beyond the classroom. “Hopefully these projects will be useful and available for public audiences,” says Yvette Shen. “We’re not just interested in how smoothly users can engage with the application, but also about the stories students are telling—the purpose of the visualization.”
All of the projects evidenced the many decisions the teams had to make to craft compelling stories from their data. User testing helped students refine their designs, leading to changes that improved accessibility and clarity. During testing and throughout the project, students gained firsthand experience in working through the many challenges of data visualization—from discerning which data sets to use, to selecting the most appropriate colors/fonts and animations/transitions, to figuring out how to split coding responsibilities among multiple developers.
With data analytics skills increasingly in demand with employers, Ohio State has made the preparation of a data analytics-savvy workforce a priority. “The new Collaborative Design course is a great way for students to learn the fundamentally critical skill of communicating the insights that data can share,” says TDAI Interim Executive Director Raghu Machiraju. “It’s not enough to analyze the data. Industry wants you to be able to show why it matters.”