Publikation:

Identifying Patterns and Anomalies within Spatiotemporal Water Sampling Data

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Datum

2018

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http://nbn-resolving.de/urn:nbn:de:bsz:352-2-piejpe1o6sbc6
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Published

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IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2018 MC2). 2018

Zusammenfassung

This paper presents our solution to the Mini Challenge 2 (MC2) of the VAST Challenge 2018. We will analyze the provided data set and introduce our visualization tool, which was implemented and tailored to the tasks given by MC2. The tool combines the power of stream graphs, innovative glyph visualizations, box plots, sparklines, heat maps and cross-filter strategies. It allows identifying patterns and anomalies within the provided data set.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Konferenz

IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2018 MC2), 21. Okt. 2018 - 26. Okt. 2018, 2018
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ISO 690PILJEK, Isabel, Giuliana DEHN, Jannik FRAUENDORF, Ziad SALEM, Yerzhan NIYAZBAYEV, Juri F. BUCHMÜLLER, Eren CAKMAK, Wolfgang JENTNER, Florian STOFFEL, Daniel A. KEIM, 2018. Identifying Patterns and Anomalies within Spatiotemporal Water Sampling Data. IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2018 MC2). 2018, 21. Okt. 2018 - 26. Okt. 2018. In: IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2018 MC2). 2018
BibTex
@inproceedings{Piljek2018Ident-45038,
  year={2018},
  title={Identifying Patterns and Anomalies within Spatiotemporal Water Sampling Data},
  url={https://scibib.dbvis.de/publications/view/791},
  booktitle={IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2018 MC2)},
  author={Piljek, Isabel and Dehn, Giuliana and Frauendorf, Jannik and Salem, Ziad and Niyazbayev, Yerzhan and Buchmüller, Juri F. and Cakmak, Eren and Jentner, Wolfgang and Stoffel, Florian and Keim, Daniel A.}
}
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Interner Vermerk

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Kontakt
URL der Originalveröffentl.
https://scibib.dbvis.de/publications/view/791

Prüfdatum der URL

2019-02-14

Prüfungsdatum der Dissertation

Finanzierungsart

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