Visual-Interactive Exploration of Relations Between Time-Oriented Data and Multivariate Data
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Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
The analysis of large, multivariate data sets is challenging, especially when some of these data objects are timeoriented. 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.
Description
@inproceedings{10.2312:eurova.20161124,
booktitle = {EuroVis Workshop on Visual Analytics (EuroVA)},
editor = {Natalia Andrienko and Michael Sedlmair},
title = {{Visual-Interactive Exploration of Relations Between Time-Oriented Data and Multivariate Data}},
author = {Bernard, Jürgen and Sessler, David and Steiger, Martin and Spott, Martin and Kohlhammer, Jörn},
year = {2016},
publisher = {The Eurographics Association},
ISSN = {-},
ISBN = {978-3-03868-016-1},
DOI = {10.2312/eurova.20161124}
}