Publikation:

Time Series Projection to Highlight Trends and Outliers

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Cakmak_2-lhh4jf6w9x756.pdf
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Datum

2018

Autor:innen

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

URI (zitierfähiger Link)
http://nbn-resolving.de/urn:nbn:de:bsz:352-2-lhh4jf6w9x756
DOI (zitierfähiger Link)
ArXiv-ID

Internationale Patentnummer

Link zur Lizenz
Urheberrechtlich geschützt

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung
Open Access Green

Sammlungen

Informatik und Informationswissenschaft: Publikationen
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

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.

Zusammenfassung in einer weiteren Sprache

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
Rezension
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Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Verknüpfte Datensätze

Zitieren

ISO 690CAKMAK, 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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Interner Vermerk

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Kontakt
URL der Originalveröffentl.
https://scibib.dbvis.de/publications/view/794

Prüfdatum der URL

2019-02-14

Prüfungsdatum der Dissertation

Finanzierungsart

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