@inproceedings{Fischer2012Realt-22275,
  year={2012},
  doi={10.1145/2245276.2245432},
  title={Real-time visual analytics for event data streams},
  isbn={978-1-4503-0857-1},
  publisher={ACM Press},
  address={New York, New York, USA},
  booktitle={Proceedings of the 27th Annual ACM Symposium on Applied Computing - SAC '12},
  pages={801--806},
  author={Fischer, Fabian and Mansmann, Florian and Keim, Daniel A.}
}

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    <dcterms:bibliographicCitation>SAC '12 Proceedings of the 27th Annual ACM Symposium on Applied Computing. - New York, NY : ACM, 2012. - S. 801-806. - ISBN 978-1-450-30857-1</dcterms:bibliographicCitation>
    <dcterms:abstract xml:lang="eng">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 to name just a few. 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. This paper presents a system to tackle some of the visualization challenges when analyzing such dynamic event data streams. In particular, we introduce the Event Visualizer, 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. Data streams with logging data from a computer network are used as a case study to demonstrate the advantages of visual exploration.</dcterms:abstract>
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    <dc:creator>Keim, Daniel A.</dc:creator>
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    <dc:contributor>Keim, Daniel A.</dc:contributor>
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    <dc:contributor>Fischer, Fabian</dc:contributor>
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