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dc.contributor.authorRafael, Joãoen_US
dc.contributor.authorMoreira, Joãoen_US
dc.contributor.authorMendes, Danielen_US
dc.contributor.authorAlves, Márioen_US
dc.contributor.authorGonçalves, Danielen_US
dc.contributor.editorAgus, Marco and Garth, Christoph and Kerren, Andreasen_US
dc.date.accessioned2021-06-12T11:03:32Z
dc.date.available2021-06-12T11:03:32Z
dc.date.issued2021
dc.identifier.isbn978-3-03868-143-4
dc.identifier.urihttps://doi.org/10.2312/evs.20211058
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evs20211058
dc.description.abstractThe availability of devices that can record locations and are connected to the Internet creates a huge amount of geospatial data that are continuously streamed. The informative visualization of such data is a challenging problem, given their sheer volume, and the real-time nature of the incoming stream. A simple approach like plotting all datapoints would generate visual noise, and not scale well. To tackle this problem, we have developed a visualization technique based on graceful degradation along three overlaid time periods (ongoing, recent, and history), each with a different visual idiom. A usability test of the proposed technique showed promising results.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectVisualization
dc.subjectVisual analytics
dc.subjectGeographic visualization
dc.titleGraceful Degradation for Real-time Visualization of Streaming Geospatial Dataen_US
dc.description.seriesinformationEuroVis 2021 - Short Papers
dc.description.sectionheadersAnalytics and Applications
dc.identifier.doi10.2312/evs.20211058
dc.identifier.pages73-77


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