Poster: Using Non-Photorealistic Rendering Techniques for the Visualization of Uncertainty

The whole process of information visualization from data acquisition to the final image includes sources of uncertainties (e.g., during measuring, aggregation, sampling, mapping,. . . ) that may significantly influence the assumptions about the data and the decisions made. Although there is no universal representation of uncertainties, a somehow common approach is to use fuzzy or blurred representations of that data. In this work, we use nonphotorealistic rendering (NPR) as it offers different parameterizable techniques to produce fuzzy representations – for the purpose of a more widespread uncertainty visualization. We demonstrate our approach by two exemplary NPR-techniques applied to information visualization to visualize uncertainties along with the related data.