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Visual-interactive exploration of relations between time-oriented data and multivariate data

: Bernard, Jürgen; Sessler, David; Steiger, Martin; Spott, Martin; Kohlhammer, Jörn


Andrienko, Natalia (Ed.); Sedlmaier, Michael (Ed.) ; European Association for Computer Graphics -EUROGRAPHICS-:
EuroVis Workshop on Visual Analytics, EuroVA 2016 : Groningen, the Netherlands, 6-10 June 2016
Aire-la-Ville: Eurographics Association, 2016
ISBN: 978-3-03868-016-1
International Workshop on Visual Analytics (EuroVA) <7, 2016, Groningen>
Eurographics Conference on Visualization (EuroVis) <18, 2016, Groningen>
Fraunhofer IGD ()
user interfaces; user-centered design; Visual analytics; visual data mining; information visualization; multimodality; Guiding Theme: Digitized Work; Guiding Theme: Smart City; Research Area: Human computer interaction (HCI)

The analysis of large, multivariate data sets is challenging, especially when some of these data objects are time oriented. Exploring relationships between multivariate and temporal information, e.g., to identify patterns that support decision making is an important industrial analysis task. The target group of this design study are data analysts aiming at detecting fault patterns in a telecommunications network in order to spend maintenance budget more effectively. We present a visual analytics tool that provides overviews of multivariate data sets and associated time series. Users can select data subsets of interest in both attribute data and clustered time series data. Linked views consequently support the identification of relations between the two spaces. To ensure usefulness, the tool was designed in an iterative way, based on a careful characterization of the data, users, and tasks. A usage scenario demonstrates the applicability of the approach.