Responsive Thinwire Visualization of Large Geographic Datasets
Author: Kenneth Been
Advisor: Chee Yap

Abstract

This thesis describes a web-based, responsive, zooming and panning visual- ization system for a full-featured geographic description of the United States. Current web-based map servers provide, from a visualization standpoint, little more than one static image per page, with hyperlinks for navigation; continuous zooming and panning requires locally stored data. Our primary contribution is a multi-threaded, scalable and responsive client-server architecture that responds to user requests as naturally and quickly as possible, regardless of network band- width reliability. This architecture can be generalized for use in other applica- tions, including non-geographic ones. To this we add a scalable and exible user interface for navigation of multi-scale geographic data, with intuitive zooming and panning, pop-up feature labels, and a user controlled tree-hierarchy of windows. We build software tools and algorithms for translating the U.S. Census Bureau's TIGER data into a format designed for speedy database retrieval and network delivery, and for generalizing the data into multiple levels of detail. Because of anomalies in the TIGER data, this processing requires some human intervention.