Evaluating Interactive Comparison Techniques in a Multiclass Density Map for Visual Crime Analytics

dc.contributor.authorSvicarovic, Lukasen_US
dc.contributor.authorParra, Denisen_US
dc.contributor.authorLobo, María Jesúsen_US
dc.contributor.editorAgus, Marco and Garth, Christoph and Kerren, Andreasen_US
dc.date.accessioned2021-06-12T11:03:33Z
dc.date.available2021-06-12T11:03:33Z
dc.date.issued2021
dc.description.abstractTechniques for presenting objects spatially via density maps have been thoroughly studied, but there is lack of research on how to display this information in the presence of several classes, i.e., multiclass density maps. Moreover, there is even less research on how to design an interactive visualization for comparison tasks on multiclass density maps. One application domain which requires this type of visualization for comparison tasks is crime analytics, and the lack of research in this area results in ineffective visual designs. To fill this gap, we study four types of techniques to compare multiclass density maps, using car theft data. The interactive techniques studied are swipe, translucent overlay, magic lens, and juxtaposition. The results of a user study (N=32) indicate that juxtaposition yields the worst performance to compare distributions, whereas swipe and magic lens perform the best in terms of time needed to complete the experiment. Our research provides empirical evidence on how to design interactive idioms for multiclass density spatial data, and it opens a line of research for other domains and visual tasks.en_US
dc.description.sectionheadersAnalytics and Applications
dc.description.seriesinformationEuroVis 2021 - Short Papers
dc.identifier.doi10.2312/evs.20211059
dc.identifier.isbn978-3-03868-143-4
dc.identifier.pages79-83
dc.identifier.urihttps://doi.org/10.2312/evs.20211059
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evs20211059
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectEmpirical studies in visualization
dc.subjectVisual analytics
dc.titleEvaluating Interactive Comparison Techniques in a Multiclass Density Map for Visual Crime Analyticsen_US
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