QuestVis and MDSteer: The Visualization of High-Dimensional Environmental Sustainability Data

Abstract The visualization of large high-dimensional,datasets is an active topic within the research area of information visualization (infovis), a research area that studies the visual representations,of complex,abstract datasets. My thesis presents two infovis systems,that were motivated,by the desire to explore a 294-dimensional,environmental sustainability dataset. Our collaborators developed,the environmental,dataset from expert knowledge on ecological, economical, and social systems which were used to model,future scenarios consisting of 294 measures,of environmental,sustainability such as urban population, water supply levels, or tonnes of waste. Since these complex,systems,and large datasets are difficult for a non-expert user to comprehend, we developed QuestVis, a tool that applies infovis theories and techniques to improve,the comprehensibility during exploration,of the environmental,dataset. The tool consists of three components: the input panel, the Multiscale Dimension Visualizer (MDV), and the Scenario Space Explorer (SSE). The MDV presents up to ten 294-dimensional future scenarios simultaneously,on the screen to enable users to get a quick overview,of the data. The simultaneous,presentation also enables users to compare,multiple future scenarios side-by-side. The SSE presents the space of all 120 000 future scenarios in an interactive two-dimensional layout which,provides the user an overview,of the possibilities. The SSE is tightly coupled,with