Name
Abstract | ||
|---|---|---|
Epidemiologists struggle to integrate complex information about the incidence and spread of disease, in relation to population density and other demographic conditions, at geographical scales ranging from global air travel down to local commuting. A partial solution overlays air travel as arcs above color-coded maps. However, commuting is not shown and it is often challenging to understand changing relationships due to the visual complexity arcs introduce. Moreover, when region sizes and shapes vary their color-codings become difficult to perceive. We introduce three visualizations which combine representations of population, movement, and disease spread at a local scale that is consistent with a zoomable global scale: (1) a map with commuting border encodings, (2) a centroidal Voronoi tessellation morphing technique, and (3) a meta-layout showing commuting alongside air travel. Our work provides mid-level abstractions that expert epidemiologists can use for insights into contagion. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2702613.2725459 | CHI Extended Abstracts |
Keywords | Field | DocType |
epidemiology,miscellaneous,geographic/geospatial data,emergency management,visualization,graph/network data | Data science,Visual complexity,Morphing,Population,Data mining,Centroidal Voronoi tessellation,Visualization,Local scale,Computer science,Air travel,Human–computer interaction | Conference |
Citations | PageRank | References |
1 | 0.38 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cody Dunne | 1 | 437 | 27.88 |
| Michael J. Muller | 2 | 2310 | 303.58 |
| Nicola Perra | 3 | 21 | 1.91 |
| Mauro Martino | 4 | 1 | 1.06 |