Real-Time Visual Analytics for Event Data Streams
Real-time analysis of data streams has become an important factor for success in many domains such as server and system administration, news analysis and finance. Introducing real-time visual analytics into such application areas promises a lot of benefits since the rate of new incoming information often exceeds human perceptual limits when displayed linearly in raw formats such as textual lines and automatic aggregation often hides important details.
We present a system to tackle some of the visualization challenges when analyzing such dynamic event data streams. In particular, we introduce the Event Visualizer in 2011, which is a loosely coupled modular system for collecting, processing, analyzing and visualizing dynamic real-time event data streams. Due to the variety of different analysis tasks the system provides an extensible framework with several interactive linked visualizations to focus on different aspects of the event data stream.
The framework was successfully used in the Honeynet Forensic Challenge.