Record Details
Automation and Evaluation of Graduated Dot Maps
ScholarsArchive at Oregon State University
| Field | Value |
|---|---|
| Title | Automation and Evaluation of Graduated Dot Maps |
| Names |
Arnold, Nicholas D.
(creator) Jenny, Bernhard J. (advisor) |
| Date Issued | 2015-06-15 (iso8601) |
| Note | Graduation date: 2016 |
| Abstract | Dot mapping is a traditional method for visualizing quantitative data, but current automated dot mapping techniques are limited. The most common automated method places dots pseudo-randomly within enumeration areas, which can result in overlapping dots and very dense dot clusters for areas with large values. These issues affect users’ ability to estimate values. Graduated dot maps use dots with different sizes that represent different values. With graduated dot maps the number of dots on a map is smaller and the likelihood of overlapping dots is smaller. This research introduces an automated method of generating graduated dot maps that arranges dots with blue noise patterns to avoid overlapping dots and uses clustering algorithms to replace densely-packed dots with dots of larger sizes. A user study comparing graduated dot maps, pseudo-random dot maps, blue noise dot maps, and area-proportional circle maps with almost 300 participants was conducted. Results indicate that map-users can interpret graduated dot maps more accurately than the other map types. In addition, map users appear to prefer graduated dot maps to the other map types. These findings suggest that graduated dot maps are more effective and more appealing than conventional dot maps. |
| Genre | Thesis/Dissertation |
| Topic | graduated dot map |
| Identifier | http://hdl.handle.net/1957/56331 |
