Cindy Xiong Bearfield Receives NSF CAREER Award for Work Establishing Trust in Data Visualizations

Manning College of Information and Computer Sciences (CICS) Assistant Professor Cindy Xiong Bearfield has received an NSF CAREER award totaling $631,846 to develop a formalized model to measure trust in human-data interaction and enhance critical thinking between humans and data in visual data communications. 

Data visualizations leverage the strength of our visual perceptual system to process information to help us communicate information more efficiently. However, many decisions go into designing a visualization – ranging from decisions about the visual styles of a chart to what background information to provide. Effective design decisions can lead to powerful and intuitive processing by a visualization reader, but poor choices can leave the key patterns misunderstood, stymie critical thinking with data, and leave the visualization reader vulnerable to biases and misinformation.  

For Bearfield, this raises important questions about how we can design visualizations to encourage critical thinking and afford trust.  

“The visualization community does not yet have a systematic understanding of factors that impact trust in visualization design nor a formalized model of how trust is measured and established between humans and data,” explains Bearfield. “Ideally, we want human readers to engage in calibrated trust when interacting with data visualizations, which involves critically evaluating the information, rather than unconditionally dismissing or accepting it. At the same time, we want to support visualization creators to design visualizations that elicit calibrated trust.” 

Using a multidisciplined approach, Bearfield’s project will work to formally define, understand, and model trust in visual data communication. First, using theories and research methods from the social sciences, Bearfield’s team will work to produce a collection of methods that reliably measure user trust in data visualizations. Using these methods, the team will then conduct studies that identify which visualization design factors—including perceived visualization clarity, complexity, data accuracy, and the amount of data—can encourage critical thinking and calibrated trust in users while identifying which of those elements can be applied generally and which may be tied to a specific use case.  

“Because trust is contextualized—meaning that the domain and topic can also influence the effect of transparency and trust—I plan to examine the relationship between these dimensions and critical thinking across two domains: public policy and behavioral economics,” says Bearfield. “This will allow us to extract key transparency factors that improve trust in visual data communication, generate practical design guidelines, and identify domain-specific versus generalizable guidelines.” 

Finally, Bearfield and her team will develop prototype visualizations and visualization systems designed to facilitate calibrated trust, examine the effectiveness of trust guidelines, and identify ethical practices for trustworthy visual data communication. The team will also develop interdisciplinary coursework and initiatives that mobilize concepts from computer science, public policy, psychology, and behavioral economics to advance practice and education around visual data communication. 

“I hope to integrate my findings into my teaching and propose new courses at the intersection of computer science and social science while prioritizing providing research opportunities for students from underrepresented populations,” says Bearfield. “I also plan to work with policymakers and industry professionals from technology and marketing to incorporate my findings into real-world practices and disseminate design guidelines in academic publications, open-sourced code repositories, and on the web to be accessible to the general public.” 

Xiong joined the CICS faculty in 2021 after receiving a doctorate in psychology and a master’s in statistics from Northwestern University. Her current research interests sit at the intersection of data visualization, human-computer interaction, decision making, visual perception, and cognition.