Honeycomb Plots: Visual Enhancements for Hexagonal Maps
| dc.contributor.author | Trautner, Thomas | en_US |
| dc.contributor.author | Sbardellati, Maximilian | en_US |
| dc.contributor.author | Stoppel, Sergej | en_US |
| dc.contributor.author | Bruckner, Stefan | en_US |
| dc.contributor.editor | Bender, Jan | en_US |
| dc.contributor.editor | Botsch, Mario | en_US |
| dc.contributor.editor | Keim, Daniel A. | en_US |
| dc.date.accessioned | 2022-09-26T09:28:49Z | |
| dc.date.available | 2022-09-26T09:28:49Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Aggregation through binning is a commonly used technique for visualizing large, dense, and overplotted two-dimensional data sets. However, aggregation can hide nuanced data-distribution features and complicates the display of multiple data-dependent variables, since color mapping is the primary means of encoding. In this paper, we present novel techniques for enhancing hexplots with spatialization cues while avoiding common disadvantages of three-dimensional visualizations. In particular, we focus on techniques relying on preattentive features that exploit shading and shape cues to emphasize relative value differences. Furthermore, we introduce a novel visual encoding that conveys information about the data distributions or trends within individual tiles. Based on multiple usage examples from different domains and real-world scenarios, we generate expressive visualizations that increase the information content of classic hexplots and validate their effectiveness in a user study. | en_US |
| dc.description.sectionheaders | Session II | |
| dc.description.seriesinformation | Vision, Modeling, and Visualization | |
| dc.identifier.doi | 10.2312/vmv.20221205 | |
| dc.identifier.isbn | 978-3-03868-189-2 | |
| dc.identifier.pages | 65-73 | |
| dc.identifier.pages | 9 pages | |
| dc.identifier.uri | https://doi.org/10.2312/vmv.20221205 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/vmv20221205 | |
| 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 techniques; Visualization theory, concepts and paradigms | |
| dc.subject | Human centered computing | |
| dc.subject | Visualization techniques | |
| dc.subject | Visualization theory | |
| dc.subject | concepts and paradigms | |
| dc.title | Honeycomb Plots: Visual Enhancements for Hexagonal Maps | en_US |