Explorative Study on Semantically Resonant Colors for Combinations of Categories with Application to Meteorological Data
dc.contributor.author | Pelchmann, Laura | en_US |
dc.contributor.author | Bremm, Sebastian | en_US |
dc.contributor.author | Ebell, Kerstin | en_US |
dc.contributor.author | Landesberger, Tatiana von | en_US |
dc.contributor.editor | Gillmann, Christina | en_US |
dc.contributor.editor | Krone, Michael | en_US |
dc.contributor.editor | Lenti, Simone | en_US |
dc.date.accessioned | 2023-06-10T06:31:32Z | |
dc.date.available | 2023-06-10T06:31:32Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 978-3-03868-220-2 | |
dc.identifier.uri | https://doi.org/10.2312/evp.20231061 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/evp20231061 | |
dc.description.abstract | We 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.publisher | The Eurographics Association | en_US |
dc.rights | Attribution 4.0 International License | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject | CCS Concepts: Human-centered computing -> Visualization; Scientific visualization; Visualization design and evaluation methods | |
dc.subject | Human centered computing | |
dc.subject | Visualization | |
dc.subject | Scientific visualization | |
dc.subject | Visualization design and evaluation methods | |
dc.title | Explorative Study on Semantically Resonant Colors for Combinations of Categories with Application to Meteorological Data | en_US |
dc.description.seriesinformation | EuroVis 2023 - Posters | |
dc.identifier.doi | 10.2312/evp.20231061 | |
dc.identifier.pages | 33-35 | |
dc.identifier.pages | 3 pages |
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ISBN 978-3-03868-220-2