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dc.contributor.authorPelchmann, Lauraen_US
dc.contributor.authorBremm, Sebastianen_US
dc.contributor.authorEbell, Kerstinen_US
dc.contributor.authorLandesberger, Tatiana vonen_US
dc.contributor.editorGillmann, Christinaen_US
dc.contributor.editorKrone, Michaelen_US
dc.contributor.editorLenti, Simoneen_US
dc.date.accessioned2023-06-10T06:31:32Z
dc.date.available2023-06-10T06:31:32Z
dc.date.issued2023
dc.identifier.isbn978-3-03868-220-2
dc.identifier.urihttps://doi.org/10.2312/evp.20231061
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evp20231061
dc.description.abstractWe present an exploratory study of semantically resonant colors for combinations of categories. The goal is to support color selection of multi-labeled classes of classified data. We asked participants to assign colors to different categories in the meteorological domain and then to their combinations. Our results show that the colors chosen for the combinations are related to the colors for the individual categories. We also found indications that people tend to prefer darker color values for combinations of categories. Our results can be used to color code meteorological data.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Human-centered computing -> Visualization; Scientific visualization; Visualization design and evaluation methods
dc.subjectHuman centered computing
dc.subjectVisualization
dc.subjectScientific visualization
dc.subjectVisualization design and evaluation methods
dc.titleExplorative Study on Semantically Resonant Colors for Combinations of Categories with Application to Meteorological Dataen_US
dc.description.seriesinformationEuroVis 2023 - Posters
dc.identifier.doi10.2312/evp.20231061
dc.identifier.pages33-35
dc.identifier.pages3 pages


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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License