Design and Evaluation of Fractal Shapes for Hierarchy Node Identification
| Author | Mertz, Tobias; Reynolds-Ringer, Steven Lamarr; Borchert, Maria; Zimmer, Lasse; Kohlhammer, Jörn |
|---|---|
| Date | 2026 |
| Type | Conference Paper |
| Abstract | The visual analysis of hierarchical data is a well-studied subject. However, in some analysis scenarios, the hierarchical structure of a multivariate dataset merely serves as context information to the analysis of other attributes. In these cases, analysts need to be aware of data points’ locations in the hierarchical structure while viewing non-hierarchical visualizations. To that end, we propose the generation of hierarchical shapes, based on fractal-like construction rules, to uniquely identify hierarchy nodes. We explore the design space of construction rules and present various example approaches, three of which we compare quantitatively in a user study. Based on the results, we select the most promising approach and compare it in a second user study to the application of hierarchical color maps. Our findings suggest that hierarchical color maps provide a quicker first estimate for the localization of a node in the hierarchy, while our hierarchical shapes are superior for the exact identification of a node. But scalability to large hierarchies is a concern for both approaches. |
| Conference | International Symposium on Vision, Modeling, and Visualization 2026 |
| Url | https://publica.fraunhofer.de/handle/publica/524603 |
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