@inproceedings{Cakmak2018Serie-45035,
  year={2018},
  title={Time Series Projection to Highlight Trends and Outliers},
  url={https://scibib.dbvis.de/publications/view/794},
  booktitle={IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2018 MC2)},
  author={Cakmak, Eren and Seebacher, Daniel and Buchmüller, Juri F. and Keim, Daniel A.}
}

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    <dc:creator>Keim, Daniel A.</dc:creator>
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    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-02-14T12:03:32Z</dc:date>
    <dc:creator>Cakmak, Eren</dc:creator>
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    <dc:creator>Buchmüller, Juri F.</dc:creator>
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    <dcterms:title>Time Series Projection to Highlight Trends and Outliers</dcterms:title>
    <dc:contributor>Keim, Daniel A.</dc:contributor>
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    <dc:creator>Seebacher, Daniel</dc:creator>
    <dc:contributor>Seebacher, Daniel</dc:contributor>
    <dc:contributor>Buchmüller, Juri F.</dc:contributor>
    <dc:contributor>Cakmak, Eren</dc:contributor>
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    <dcterms:abstract xml:lang="eng">The goal of the VAST Challenge 2018 Mini Challenge 2 (MC 2) was to unveil the possible causes and effects of environmental pollution in the Boonsong Lekagul Wildlife Preserve. We propose the ViCCEx (Visual Chemical Contamination Explorer) system that enables to interactively explore the sparse multivariate river network sensor reading dataset to identify characteristics, trends, and outliers of the different sensor reading locations over time. The ViCCEx system uses a t-SNE projection to display an overview visualization, a sampling strategy view to highlight the overall sampling strategies of different chemical measurements at each sensor location, and various extracted statistics to highlight the evolution of chemical measurements. The three views are connected via linking and brushing, which enables to explore and identify possible pollution causes and effects in the preserve.</dcterms:abstract>
    <dcterms:issued>2018</dcterms:issued>
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