690 citations
- University of North Carolina at Chapel HillUS24 papers
- Lawrence Berkeley National LaboratoryUS7 papers
- Johns Hopkins UniversityUS4 papers
- University of Colorado AnschutzUS4 papers
- University of FloridaUS4 papers
- European Bioinformatics InstituteGB3 papers
- European Molecular Biology LaboratoryDE3 papers
- Harvard UniversityUS3 papers
- Indiana UniversityUS3 papers
- Oregon State UniversityUS3 papers
- University of ChicagoUS3 papers
- University of WashingtonUS3 papers
11 papers · 1 filter
Contextualization or Rationalization? The Effect of Causal Priors on Data Visualization Interpretation
Arran Zeyu Wang, David Borland, Estella Calcaterra +1
Understanding how individuals interpret charts is a crucial concern for visual data communication. This imperative has motivated a number of studies, including past work demonstrat…
Beyond Correlation: Incorporating Counterfactual Guidance to Better Support Exploratory Visual Analysis
Arran Zeyu Wang, David Borland, David Gotz
Providing effective guidance for users has long been an important and challenging task for efficient exploratory visual analytics, especially when selecting variables for visualiza…
Causal Priors and Their Influence on Judgements of Causality in Visualized Data
Arran Zeyu Wang, David Borland, Tabitha C. Peck +2
"Correlation does not imply causation" is a famous mantra in statistical and visual analysis. However, consumers of visualizations often draw causal conclusions when only correlati…
An Empirical Study of Counterfactual Visualization to Support Visual Causal Inference
Arran Zeyu Wang, David Borland, David Gotz
Counterfactuals -- expressing what might have been true under different circumstances -- have been widely applied in statistics and machine learning to help understand causal relat…
Using Counterfactuals to Improve Causal Inferences from Visualizations
David Borland, Arran Zeyu Wang, David Gotz
Traditional approaches to data visualization have often focused on comparing different subsets of data, and this is reflected in the many techniques developed and evaluated over th…
Enabling Longitudinal Exploratory Analysis of Clinical COVID Data
David Borland, Irena Brain, Karamarie Fecho +5
As the COVID-19 pandemic continues to impact the world, data is being gathered and analyzed to better understand the disease. Recognizing the potential for visual analytics technol…