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NStreamAware : Real-Time visual analytics for data streams (VAST Challenge 2014 MC3)

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2014

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https://doi.org/10.1109/VAST.2014.7042572
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MIN CHEN ..., , ed.. 2014 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings ; Paris, France, 9-14 October 2014. Piscataway, NJ: IEEE, 2014, pp. 373-374. ISBN 978-1-4799-6227-3. Available under: doi: 10.1109/VAST.2014.7042572

Zusammenfassung

To solve the VAST Challenge 2014 MC3 we use NStreamAware, which is our real-time visual analytics system to analyze data streams. We make use of various modern technologies like Apache Spark and others to provide high scalability and incorporate new technologies and show their use within visual analytics applications. Furthermore, we developed a web application, called NVisAware, to analyze and visualize data streams to help the analyst to focus on the most important time segments. We extracted socalled sliding slices, which are aggregated summaries calculated on a sliding window and represent them in a small-multiple like visualization containing various small visualizations (e.g., word clouds) to present an overview of the current time segment. We show how these techniques can be used to successfully solve the given tasks.

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004 Informatik

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IEEE Conference on Visual Analytics Science and Technology (VAST), 2014, 9. Okt. 2014 - 14. Okt. 2014, Paris
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ISO 690FISCHER, Fabian, 2014. NStreamAware : Real-Time visual analytics for data streams (VAST Challenge 2014 MC3). IEEE Conference on Visual Analytics Science and Technology (VAST), 2014. Paris, 9. Okt. 2014 - 14. Okt. 2014. In: MIN CHEN ..., , ed.. 2014 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings ; Paris, France, 9-14 October 2014. Piscataway, NJ: IEEE, 2014, pp. 373-374. ISBN 978-1-4799-6227-3. Available under: doi: 10.1109/VAST.2014.7042572
BibTex
@inproceedings{Fischer2014NStre-30122,
  year={2014},
  doi={10.1109/VAST.2014.7042572},
  title={NStreamAware : Real-Time visual analytics for data streams (VAST Challenge 2014 MC3)},
  isbn={978-1-4799-6227-3},
  publisher={IEEE},
  address={Piscataway, NJ},
  booktitle={2014 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings ; Paris, France, 9-14 October 2014},
  pages={373--374},
  editor={Min Chen ...},
  author={Fischer, Fabian}
}
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