ClimateVisInterviews “Being Simple on Complex Issues” – Accounts on Visual Data Communication About Climate Change (published)
We studied how climate change is communicated and understood through data visualizations by interviewing 17 experts in the fields of data visualization, science communication or climate change and 12 laypeople. Participants shared their thoughts on climate change communication and interpreted and discussed five example charts. Our analysis showed key differences in how both groups make sense of, understand, and summarize the visualizations.
Reference
Schuster, R., Gregory, K., Möller, T., & Koesten, L. (2024). “Being Simple on Complex Issues” – Accounts on Visual Data Communication About Climate Change. IEEE Transactions on Visualization and Computer Graphics, 30(9), 6598–6611. https://doi.org/10.1109/TVCG.2024.3352282
CrisisMapSensemaking Encountering Friction, Understanding Crises: How Do Digital Natives Make Sense of Crisis Maps? (published)
We studied how young, digitally native audiences make sense of crisis-related data visualizations. To understand their sensemaking, we studied online comments from a New York Times series about graphs and conducted interviews with 18 people from German-speaking countries. By analyzing both studies, we also identified where challenges arise and how emotions and trust play a role.
Reference
Koesten, L., Saske, A., Starchenko, S., & Gregory, K. (2025). Encountering Friction, Understanding Crises: How Do Digital Natives Make Sense of Crisis Maps? Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’25). April 26–May 1, 2025, Yokohama, Japan. ACM. https://doi.org/10.1145/3706598.3713520
DomainVisStudy Tensions between Preference and Performance: Designing for Visual Exploration of Multi-frequency Medical Network Data (preprint)
We worked with medical researchers to design and test two types of visualizations for brain network data from EEGs. In a study with domain experts and non-experts, we compared how well these visualizations supported understanding and task performance. While participants preferred a more aesthetic design in early tests, this did not always translate into better results in later evaluations.
Reference
Knoll, C., Koesten, L., Rigoni, I., Vulliémoz, S., Möller (2024). Tensions between Preference and Performance: Designing for Visual Exploration of Multi-frequency Medical Network Data. arXiv. https://arxiv.org/abs/2404.03965
Pathos Untangling Rhetoric, Pathos, and Aesthetics in Data Visualization (under review)
This paper explores the theoretical intersections of rhetoric, pathos, and aesthetics, with a specific focus on their implications for data visualization. While data visualization is often framed in terms of clarity, efficiency, and truthfulness, we argue that emotional engagement and aesthetic form are equally central to how data communicates and persuades. Drawing from rhetorical theory and aesthetics, we untangle the conceptual threads that link pathos, the appeal to emotion, with visual design and sensemaking in data representations.
Reference
Forthcoming. Under review. Citation will be provided upon publication.
SemanticContextExperiment Studying Semantic Context in Visualizations: Introducing Semantic Context Charts (under review)
We tested how adding context to bar charts affects how people experience and understand data. In a study with 20 participants, we compared standard bar charts to new versions that included visual cues tied to the data’s meaning. Participants found the contextual charts more engaging and easier to understand, while standard bar charts were seen as more trustworthy. Both formats supported different strengths in reading data.
Reference
Forthcoming. Under review. Citation will be provided upon publication.
SciAmInterviews Data Journeys in Popular Science: Producing Climate Change and COVID-19 Data Visualizations at Scientific American (published)
We examined how climate change and COVID-19 data visualizations are created in Scientific American using interviews with staff and visual analysis of selected charts. Focusing on data journeys, we explored how open data, collaborative practices, and editorial choices shape visualizations, and how science communicators work to counter misinformation and foster transparency.
Reference
Gregory, K., Koesten, L., Schuster, R., Möller, T., Davies, S. (2024). Data Journeys in Popular Science: Producing Climate Change and COVID-19 Data Visualizations at Scientific American. Harvard Data Science Review. https://hdsr.mitpress.mit.edu/pub/jme9l45q
SciAmMessageAnalysis Scientific American Message Analysis (under review)
We investigated how data visualizations in Scientific American communicate messages about climate change and pandemics and how these messages are interpreted. Using a mixed-methods approach, we analyzed visualizations, interpreted them as chart readers, and compared our interpretations to intended messages based on interviews with producers. We identified mismatches and proposed a typology of message types, highlighting the role of textual elements and sensemaking in communicating data effectively.
Reference
Forthcoming. Under review. Citation will be provided upon publication.
VisLiteracySurvey MAVIL: Design of a Multidimensional Assessment of Visual Data Literacy and its Application in a Representative Survey (preprint)
We developed and tested MAVIL, a multidimensional tool to assess how general audiences interpret data visualizations. The tool measures six dimensions of visual data literacy, including reading and critiquing charts. We conducted a survey with 438 participants across age and gender groups representative for Austria, using self-assessments, performance tasks, and open-ended feedback on two climate visualizations.
Reference
Saske, A., Möller, T., Koesten, L., Staudner, J., Kritzinger, S. (2024). MAVIL: Design of a Multidimensional Assessment of Visual Data Literacy and its Application in a Representative Survey. arXiv. https://arxiv.org/abs/2410.23807
VisProducerInterviews Who is the Audience? Designing Casual Data Visualizations for the “General Public” (preprint)
We explored how data visualization practitioners think about and design for lay audiences through interviews with professionals working in different settings. We found that while many practitioners care about understanding their audience, they often rely on simple metrics or feedback from colleagues. A clear definition of “Who is the audience?” and what that means for data visualization design is often lacking. Furthermore, in many settings, evaluation techniques like user testing are too expensive or time-consuming.
Reference
Schuster, R., Koesten, L., Gregory, K., Möller, T. (2023). Who is the Audience? Designing Casual Data Visualizations for the “General Public.” arXiv. https://arxiv.org/abs/2310.01935
VisWorkshops The Gulf of Interpretation: From Chart to Message and Back Again (published)
We explored how data visualizations are understood by different audiences and whether their interpretations match the intended messages. We ran workshops and interviews with groups including students, job seekers, designers, and seniors to collect feedback on eight real-world charts. Comparing their interpretations with the original message helped us identify gaps in understanding and confusion caused by unfamiliar terms or too much data.
Reference
Knoll, C., Koesten, L., Möller, T., Gregory, K. (2025). The Gulf of Interpretation: From Chart to Message and Back Again. Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’25). ACM. https://doi.org/10.1145/3706598.3713413