EuroVisShort2020

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https://diglib.eg.org/handle/10.2312/2632897

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Browsing EuroVisShort2020 by Subject "Graph drawings"

Now showing 1 - 2 of 2
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    The Effect of Graph Layout on the Perception of Graph Properties
    (The Eurographics Association, 2020) Kypridemou, Elektra; Zito, Michele; Bertamini, Marco; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    The way in which a graph is described visually is crucial for the understanding and analysis of its structure. In this study we explore how different drawing layouts affect our perception of the graph's properties. We study the perception of connectedness, tree-ness and density using four different layouts: the Circular, Grid, Planar and Spring layouts. Results show that some layouts are better than others when we need to decide whether a graph is a tree or is connected. More sophisticated algorithms, like Planar and Spring, facilitate our perception, while Circular and Grid layouts lead to performance not better than chance. However, when perceiving the density of a graph, no layout was found to be better than the others.
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    Fast Design Space Rendering of Scatterplots
    (The Eurographics Association, 2020) Santala, Simo; Oulasvirta, Antti; Weinkauf, Tino; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
    The design space of scatterplots consists of a number of parameters such as marker size and shape, image width and aspect ratio, and opacity. Different parameters yield different visual impressions of the scatterplot. Perceptual optimization of scatterplots means finding the best design parameters to support a given visualization task. This requires rendering thousands of design variations. We describe an image-based method for rendering scatterplots, which is tailored to this scenario: it enables quick updates of the design by re-using previously calculated intermediate results, and is independent of the data set size. Our approach outperforms the classic method of rendering scatterplots, i.e., drawing each marker individually onto an image, and can therefore dramatically speed up the perceptual optimization of scatterplots. We provide an open-source implementation and an online service for our method.