Visualization Support for Fusing Relational, Spatio-Temporal Data: Building Career Histories

Jim Blythe, Mithila Patwardhan, Tim Oates, Marie desJardins, Penny Rheingans

Abstract: Many real-world domains resist analysis because they are best characterized by a variety of data types, including relational, spatial, and temporal components. Examples of such domains include disease outbreaks, criminal networks, and the World-Wide Web. We present two types of visualizations based on physical metaphors that facilitate fusion, analysis, and deep understanding of relational, spatio-temporal data. The first visualization is based on the metaphor of fluid flow through elastic pipes, and the second on wave propagation. We discuss both types of visualizations in the context of fusing information about the activities of scientists over time with the goal of constructing career histories