3473041
doi
10.5281/zenodo.3473041
oai:zenodo.org:3473041
user-h_da
user-visual-trend-analytics
user-h_da-vis
Kawa Nazemi
Human-Computer Interaction & Visual Analytics Research Group, Darmstadt University of Applied Sciences
Arjan Kuijper
Department of Computer Science, TU Darmstadt, Darmstadt, Germany
Egils Ginters
Riga Technical University, Riga, Latvia
A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts
Dirk Burkhardt
Human-Computer Interaction & Visual Analytics Research Group, Darmstadt University of Applied Sciences
isbn:978-88-85741-41-6
info:eu-repo/semantics/openAccess
Other (Attribution)
Mobile Visual Analytics
Visual Trend Analysis
Decision Support Systems
Business Analytics
Human-Computer Interaction
Information Visualization
Mobile Devices
<p>The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design.</p>
CAL-TEK SRL
2019-09-18
info:eu-repo/semantics/conferencePaper
3473040
user-h_da
user-visual-trend-analytics
user-h_da-vis
v1
1579540195.900181
2124486
md5:5287159005d85b9f9c3898e0d337bfe1
https://zenodo.org/records/3473041/files/VARE2019_MobileTrendAnalytics.pdf
public
978-88-85741-41-6
Is part of
isbn
10.5281/zenodo.3473040
isVersionOf
doi
Proceedings of the International Conference of the Virtual and Augmented Reality in Education
978-88-85741-41-6
11--19
Rende, Italy
2019-09-18