Time Series Projection to Highlight Trends and Outliers

Cakmak, Eren; Seebacher, Daniel; Buchmüller, Juri F.; Keim, Daniel A.

Time Series Projection to Highlight Trends and Outliers

Dateien

Cakmak_2-lhh4jf6w9x756.pdfGröße: 349.38 KBDownloads: 402

Datum

2018

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen in

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

Zusammenfassung

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.

Fachgebiet (DDC)

004 Informatik

Schlagwörter

Human-centered computing, Visualization, Visualization application domains, Visual Analytics

Konferenz

IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2018 MC2), 21. Okt. 2018 - 26. Okt. 2018, Berlin

Zitieren

ISO 690

CAKMAK, Eren, Daniel SEEBACHER, Juri F. BUCHMÜLLER, Daniel A. KEIM, 2018. Time Series Projection to Highlight Trends and Outliers. IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2018 MC2). Berlin, 21. Okt. 2018 - 26. Okt. 2018. In: IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2018 MC2). 2018

BibTex

@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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URL der Originalveröffentl.

https://scibib.dbvis.de/publications/view/794

Prüfdatum der URL

2019-02-14

Universitätsbibliographie

Ja