xii, 80 p. : ill., maps (some col.) A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / Choropleth maps are a popular way of depicting spatial data. The map communication model, which theorizes that geographic information is transmitted from the cartographer to the map user via a map, suggests that cartographers are responsible for clearly conveying spatial data in a way all map users can understand. Map users, however, come from different places and may harbor certain regional biases. This thesis investigates whether map users tend to focus on data patterns within their home regions during the visual-search and decision-making processes when reading classed choropleth maps, thereby exhibiting an egocentric map behavior. Seventy-one subjects took a computer-based test asking them to identify various phenomena on a series of choropleth maps of the lower 48 states. The results show a weak positive effect of egocentric map behavior; subjects who lived in a particular state longer were slightly more likely to choose states nearby their home region. / Committee in Charge: Dr. Amy Lobben, Chair; Dr. Dan Gavin

Thesis (Ph. D.)--University of Wisconsin--Madison, 1970. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliography.

Presenting large amount of Multivariate Data is not a simple problem. When there are multiple correlated variables involved, it becomes difficult to comprehend data using traditional ways. Information Visualization techniques provide an interactive way to present and analyze such data. This thesis has been carried out at ABB Corporate Research, Västerås, Sweden. Use of Parallel Coordinates and Multiple Coordinated Views was has been suggested to realize interactive reporting and trending of Multivariate Data for ABB’s Network Manager SCADA system. A prototype was developed and an empirical study was conducted to evaluate the suggested design and test it for usability from an actual industry perspective. With the help of this prototype and the evaluations carried out, we are able to achieve stronger results regarding the effectiveness and efficiency of the visualization techniques used. The results confirm that such interfaces are more effective, efficient and intuitive for filtering and analyzing Multivariate Data.