MotionGlyphs: Visual Abstraction of Spatio-Temporal Networks in Collective Animal Behavior

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dc.contributor.authorCakmak, Erenen_US
dc.contributor.authorSchäfer, Hannaen_US
dc.contributor.authorBuchmüller, Jurien_US
dc.contributor.authorFuchs, Johannesen_US
dc.contributor.authorSchreck, Tobiasen_US
dc.contributor.authorJordan, Alexen_US
dc.contributor.authorKeim, Daniel A.en_US
dc.contributor.editorViola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatianaen_US
dc.date.accessioned2020-05-24T12:59:59Z
dc.date.available2020-05-24T12:59:59Z
dc.date.issued2020
dc.description.abstractDomain experts for collective animal behavior analyze relationships between single animal movers and groups of animals over time and space to detect emergent group properties. A common way to interpret this type of data is to visualize it as a spatio-temporal network. Collective behavior data sets are often large, and may hence result in dense and highly connected node-link diagrams, resulting in issues of node-overlap and edge clutter. In this design study, in an iterative design process, we developed glyphs as a design for seamlessly encoding relationships and movement characteristics of a single mover or clusters of movers. Based on these glyph designs, we developed a visual exploration prototype, MotionGlyphs, that supports domain experts in interactively filtering, clustering, and animating spatio-temporal networks for collective animal behavior analysis. By means of an expert evaluation, we show how MotionGlyphs supports important tasks and analysis goals of our domain experts, and we give evidence of the usefulness for analyzing spatio-temporal networks of collective animal behavior.en_US
dc.description.number3
dc.description.sectionheadersVisualization Applications and Machine Learning
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume39
dc.identifier.doi10.1111/cgf.13963
dc.identifier.issn1467-8659
dc.identifier.pages63-75
dc.identifier.urihttps://doi.org/10.1111/cgf.13963
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13963
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/]
dc.titleMotionGlyphs: Visual Abstraction of Spatio-Temporal Networks in Collective Animal Behavioren_US
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