FR-glyphs for Multidimensional Categorical Data
| dc.contributor.author | Canlon, Delorean C. | en_US |
| dc.contributor.author | Paulovich, Fernando | en_US |
| dc.contributor.author | Tennekes, Martijn | en_US |
| dc.contributor.editor | Tominski, Christian | en_US |
| dc.contributor.editor | Waldner, Manuela | en_US |
| dc.contributor.editor | Wang, Bei | en_US |
| dc.date.accessioned | 2024-05-17T18:47:42Z | |
| dc.date.available | 2024-05-17T18:47:42Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Multivariate categorical data analysis is challenging, especially when geographical information is present. Despite the widespread existence of such datasets, the current visualization solutions only typically represent frequencies of attributes, which can be misleading if uncorrelated attributes exist. We present the frequency-relation-glyphs, or FR-glyphs, as an alternative solution for these issues. FR-glyphs can (1) show deviations in the attribute's frequencies and (2) relations between combined sets of attributes. Furthermore, they can be added to geographical maps to compare multiple regions, such as provinces. We used the Bestand geRegistreerde Ongevallen in Nederland (BRON) dataset, which includes bicycle incidents, to show the usefulness of the FR-glyphs and evaluate them with stakeholders. | en_US |
| dc.description.sectionheaders | Interaction and Space | |
| dc.description.seriesinformation | EuroVis 2024 - Short Papers | |
| dc.identifier.doi | 10.2312/evs.20241061 | |
| dc.identifier.isbn | 978-3-03868-251-6 | |
| dc.identifier.pages | 5 pages | |
| dc.identifier.uri | https://doi.org/10.2312/evs.20241061 | |
| dc.identifier.uri | https://diglib.eg.org/handle/10.2312/evs20241061 | |
| 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 design and evaluation methods | |
| dc.subject | Human centered computing → Visualization design and evaluation methods | |
| dc.title | FR-glyphs for Multidimensional Categorical Data | en_US |