Publikation:

Off-Screen Visualization Perspectives : Tasks and Challenges

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2015

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Jäckle, Dominik
Kwon, Bum Chul
Keim, Daniel A.

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Published

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Symposium on Visualization in Data Science (VDS) at IEEE VIS 2015. 2015

Zusammenfassung

The visual exploration of large data spaces often requires zooming and panning operations to obtain details. However, drilling down to see details results in the loss of contextual overview. Existing overview-plus-detail approaches provide context while the user examines details, but typically suffer from distortion or overplotting. This is why, there is great potential for off-screen visualization. Off-screen visualization is a family of techniques which provide data-driven context with the aid of visual proxies. Visual proxies can be visually encoded and adapted to the necessary data context with respect to scalability and visualization of high dimensional data. In this paper, we uncover the potential of off-screen visualization in visual data exploration by introducing its application examples to different domains through three derived scenarios. Furthermore, we categorize supporting tasks of off-screen visualizations and show areas of improvement. Then, we derive research challenges of offscreen visualizations and draw our perspectives on the issues for future research. This paper will provide guidance for future research on off-screen visualization techniques in visual data analysis.

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004 Informatik

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Off-screen Visualization

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Symposium on Visualization in Data Science (VDS) at IEEE VIS 2015, 26. Okt. 2015, Chicago, Illinois
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ISO 690JÄCKLE, Dominik, Bum Chul KWON, Daniel A. KEIM, 2015. Off-Screen Visualization Perspectives : Tasks and Challenges. Symposium on Visualization in Data Science (VDS) at IEEE VIS 2015. Chicago, Illinois, 26. Okt. 2015. In: Symposium on Visualization in Data Science (VDS) at IEEE VIS 2015. 2015
BibTex
@inproceedings{Jackle2015OffSc-45147,
  year={2015},
  title={Off-Screen Visualization Perspectives : Tasks and Challenges},
  url={https://scibib.dbvis.de/publications/view/632},
  booktitle={Symposium on Visualization in Data Science (VDS) at IEEE VIS 2015},
  author={Jäckle, Dominik and Kwon, Bum Chul and Keim, Daniel A.}
}
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