Browsing by Author "Chen, Min"

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    Automatic Improvement of Continuous Colormaps in Euclidean Colorspaces
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Nardini, Pascal; Chen, Min; Böttinger, Michael; Scheuermann, Gerik; Bujack, Roxana; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    Colormapping is one of the simplest and most widely used data visualization methods within and outside the visualization community. Uniformity, order, discriminative power, and smoothness of continuous colormaps are the most important criteria for evaluating and potentially improving colormaps. We present a local and a global automatic optimization algorithm in Euclidean color spaces for each of these design rules in this work. As a foundation for our optimization algorithms, we used the CCC-Tool colormap specification (CMS); each algorithm has been implemented in this tool. In addition to synthetic examples that demonstrate each method's effect, we show the outcome of some of the methods applied to a typhoon simulation.
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    Design Space of Origin-Destination Data Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Tennekes, Martijn; Chen, Min; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    Visualization is an essential tool for observing and analyzing origin-destination (OD) data, which encodes flows between geographic locations, e.g., in applications concerning commuting, migration, and transport of goods. However, depicting OD data often encounter issues of cluttering and occlusion. To address these issues, many visual designs feature data abstraction and visual abstraction, such as node aggregation and edge bundling, resulting in information loss. The recent theoretical and empirical developments in visualization have substantiated the merits of such abstraction, while confirming that viewers' knowledge can alleviate the negative impact due to information loss. It is thus desirable to map out different ways of losing and adding information in origin-destination data visualization (ODDV).We therefore formulate a new design space of ODDV based on the categorization of informative operations on OD data in data abstraction and visual abstraction. We apply this design space to existing ODDV methods, outline strategies for exploring the design space, and suggest ideas for further exploration.