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2014 IEEE Conference on Visual Analytics Science and Technology (VAST) (2014)
Paris, France
Oct. 25, 2014 to Oct. 31, 2014
ISBN: 978-1-4799-6227-3
pp: 301-302
Fabian Fischer , Data Analysis and Visualization Group University of Konstanz, Germany
Florian Stoffel , Data Analysis and Visualization Group University of Konstanz, Germany
Sebastian Mittelstadt , Data Analysis and Visualization Group University of Konstanz, Germany
Tobias Schreck , Data Analysis and Visualization Group University of Konstanz, Germany
Daniel A. Keim , Data Analysis and Visualization Group University of Konstanz, Germany
ABSTRACT
Gaining insights from different heterogeneous data sources is one of the biggest challenges in decision making support. The large volumes of data can only be combined by sophisticated automatic methods. However, unexpected patterns can only be identified with the help of human intuition. In this paper, we present our visual analytics work-flows and tools to process heterogeneous data such as social networks, text streams, and geo-temporal data. We apply these tools on the VAST Challenge data and present our findings and assumptions that we identified in our analysis.
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CITATION

F. Fischer, F. Stoffel, S. Mittelstadt, T. Schreck and D. A. Keim, "Using visual analytics to support decision making to solve the Kronos incident (VAST challenge 2014)," 2014 IEEE Conference on Visual Analytics Science and Technology (VAST), Paris, France, 2014, pp. 301-302.
doi:10.1109/VAST.2014.7042537
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