A Visual Analytics Approach to Understanding Spatiotemporal Hotspots

As data sources become larger and more complex, the ability to effectively explore and analyze patterns amongst varying sources becomes a critical bottleneck in analytic reasoning. Incoming data contains multiple variables, high signal to noise ratio, and a degree of uncertainty, all of which hinder exploration, hypothesis generation/exploration, and decision making. To facilitate the exploration of such data, advanced tool sets are needed that allow the user to interact with their data in a visual environment that provides direct analytic capability for finding data aberrations or hotspots. In this paper, we present a suite of tools designed to facilitate the exploration of spatiotemporal datasets. Our system allows users to search for hotspots in both space and time, combining linked views and interactive filtering to provide users with contextual information about their data and allow the user to develop and explore their hypotheses. Statistical data models and alert detection al...

• Type: Journal
• Year: 2010
• Where: TVCG
• Authors: Ross Maciejewski, Stephen Rudolph, Ryan Hafen, Ahmad M. Abusalah, Mohamed Yakout, Mourad Ouzzani, William S. Cleveland, Shaun J. Grannis, David S. Ebert
• Keywords: Direct Analytic Capability, Exploration, Tools, TVCG 2010