Name
Abstract | ||
|---|---|---|
ABSTRACTTopoText is a context-preserving technique for visualizing text data for multi-scale spatial aggregates to gain insight into spatial phenomena. Conventional exploration requires users to navigate across multiple scales but only presents the information related to the current scale. This limitation potentially adds more steps of interaction and cognitive overload to the users. TopoText renders multi-scale aggregates into a single visual display combining novel text-based encoding and layout methods that draw labels along the boundary or filled within the aggregates. The text itself not only summarizes the semantics at each individual scale, but also indicates the spatial coverage of the aggregates and their underlying hierarchical relationships. We validate TopoText with both a user study as well as several application examples. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3173574.3173611 | Conference on Human Factors in Computing Systems |
Keywords | Field | DocType |
Geospatial visualization, text visualization, typographic map, context preservation, multi-scale analysis | Geospatial visualization,Data exploration,Computer science,Human–computer interaction,Cognitive load,Semantics,Encoding (memory) | Conference |
Citations | PageRank | References |
1 | 0.34 | 31 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiawei Zhang | 1 | 806 | 72.17 |
| Chittayong Surakitbanharn | 2 | 2 | 1.02 |
| Niklas Elmqvist | 3 | 2065 | 98.35 |
| Ross Maciejewski | 4 | 542 | 36.54 |
| Zhenyu Cheryl Qian | 5 | 5 | 4.87 |
| David S. Ebert | 6 | 2056 | 232.34 |