Forecasting Hotspots - A Predictive Analytics Approach

—Current visual analytics systems provide users with the means to explore trends in their data. Linked views and interactive displays provide insight into correlations among people, events, and places in space and time. Analysts search for events of interest through statistical tools linked to visual displays, drill down into the data, and form hypotheses based upon the available information. However, current systems stop short of predicting events. In spatiotemporal data, analysts are searching for regions of space and time with unusually high incidences of events (hotspots). In the cases where hotspots are found, analysts would like to predict how these regions may grow in order to plan resource allocation and preventative measures. Furthermore, analysts would also like to predict where future hotspots may occur. To facilitate such forecasting, we have created a predictive visual analytics toolkit that provides analysts with linked spatiotemporal and statistical analytic views. Our...

• Type: Journal
• Year: 2011
• Where: TVCG
• Authors: Ross Maciejewski, Ryan Hafen, Stephen Rudolph, Stephen G. Larew, Michael A. Mitchell, William S. Cleveland, David S. Ebert
• Keywords: Predictive Visual Analytics, TVCG 2011, Visual Analytics, —Current Visual Analytics