EuroVisShort2015

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https://diglib.eg.org/handle/10.2312/12463

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Browsing EuroVisShort2015 by Subject "General"

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    Visual Analytics of Work Behavior Data - Insights on Individual Differences
    (The Eurographics Association, 2015) Koldijk, Saskia; Bernard, Jürgen; Ruppert, Tobias; Kohlhammer, Jörn; Neerincx, Mark; Kraaij, Wessel; E. Bertini and J. Kennedy and E. Puppo
    Stress in working environments is a recent concern. We see potential in collecting sensor data to detect patterns in work behavior with potential danger to well-being. In this paper, we describe how we applied visual analytics to a work behavior dataset, containing information on facial expressions, postures, computer interactions, physiology and subjective experience. The challenge is to interpret this multi-modal low level sensor data. In this work, we alternate between automatic analysis procedures and data visualization. Our aim is twofold: 1) to research the relations of various sensor features with (stress related) mental states, and 2) to develop suitable visualization methods for insight into a large amount of behavioral data. Our most important insight is that people differ a lot in their (stress related) work behavior, which has to be taken into account in the analyses and visualizations.
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    Visualizing Dynamic Brain Networks Using an Animated Dual-Representation
    (The Eurographics Association, 2015) Ma, Chihua; Kenyon, Robert V.; Forbes, Angus G.; Berger-Wolf, Tanya; Slater, Bernard J.; Llano, Daniel A.; E. Bertini and J. Kennedy and E. Puppo
    Dynamic network visualization has been a challenging topic for dynamic networks analysis, especially for spatially embedded networks like brain networks. In this paper, we present an animated interactive visualization design that combines enhanced node-link diagrams and distance matrix layouts to assist neuroscientists in their exploration of dynamic brain networks and that enables them to understand how functional connections relate to the spatial structure of the brain. Our visualization also provides the ability to observe the evolution of a network, the change in the community identities, and node behavior over time.