The Noisy Work of Uncertainty Visualization

Better representation of the uncertainty in a data visualization is a focus of recent research activity. A problem with the current literature is that there is a lack of clarity about the definition of uncertainty and what it means to represent it in a plot. This confusion has led to conflicting results in the literature, especially in experiments that assess the effectiveness of different uncertainty representations. In this review, we summarize the current literature, provide workable definitions, and illustrate these definitions with examples. In doing so, we ask what it really takes to achieve transparency in statistical graphics. We hope that it will be useful for guiding new graphics methodology and experimental research.