We are excited to share that our paper, titled “The Gulf of Interpretation: From Chart to Message and Back Again,” has been accepted at CHI'25 (ACM CHI Conference on Human Factors in Computing Systems). Christian Knoll will present the paper at the conference in Yokohama, Japan, in late April.

Charts are used to communicate data visually, but designing an effective chart that a broad set of people can understand is challenging. Usually, we do not know whether a chart's intended message aligns with the message readers perceive. The paper reports on a mixed-methods study with data journalists who create charts for popular news media, as well as diverse audiences who act as readers of the charts. Based on workshops and interviews with school and university students, job seekers, designers, and senior citizens, we collected perceived messages and feedback on eight real-world data visualizations. We analyzed these messages and compared them to the intended messages of the journalists.

This work helps to understand the gulf that can exist between messages encoded by the chart producer and viewer interpretations. The results from our work underline the difficulty of complex charts such as stacked bar charts and Sankey diagrams. We observed that consumers are often overwhelmed with the amount of data provided, and unfamiliar terms lead to confusion. On the chart producers' side, strong conventions shaped visual encoding choices, but these did not always seem to benefit chart consumers

Based on our findings, we derived practical implications for the visualization and human-computer interaction community:

• Rethink conventional chart types
• Use familiar and basic chart types
• Collaborate on visualization design
• Test the chart
• Aim for diversity

Citation to paper: Christian Knoll, Torsten Möller, Kathleen Gregory, and Laura Koesten. 2025. The Gulf of Interpretation: From Chart to Message and Back Again. In CHI Conference on Human Factors in Computing Systems (CHI '25), April 26-May 1, 2025, Yokohama, Japan. ACM, New York, NY, USA, 17 pages. DOI: TBA

Keywords: Mixed-methods study, Visualization, Messages, Popular media, Data journalists, Diverse audience, Sensemaking.