FR-glyphs for Multidimensional Categorical Data
No Thumbnail Available
Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
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.
Description
CCS Concepts: Human-centered computing → Visualization design and evaluation methods
@inproceedings{10.2312:evs.20241061,
booktitle = {EuroVis 2024 - Short Papers},
editor = {Tominski, Christian and Waldner, Manuela and Wang, Bei},
title = {{FR-glyphs for Multidimensional Categorical Data}},
author = {Canlon, Delorean C. and Paulovich, Fernando and Tennekes, Martijn},
year = {2024},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-251-6},
DOI = {10.2312/evs.20241061}
}