Tracking relationships among animals over space and time is common in the study of collective animal behavior. 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. Visual analytics experts Eren Cakmak and Daniel Keim created MotionGlyphs, which abstracts relationships and aggregates movers into groups to reduce visual clutter and highlight the social phenotype of group members. Working with biologist Alex Jordan, who studies social interactions in fish, they show that the visual exploration tool can assit in interactively filtering, clustering, and animating spatio-temporal networks in collective behaviour research.
Cite the tool
Cakmak E, Schäfer H, Buchmüller J, Fuchs J, Schreck T, Jordan A, Keim D (2020) MotionGlyphs: Visual Abstraction of Spatio-Temporal Networks in Collective Animal Behavior. In Eurographics Conference on Visualization (EuroVis) 2020. DOI: 10.1111/cgf.13963