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Visual Methods for Analyzing Time-Oriented Data
January/February 2008 (vol. 14 no. 1)
pp. 47-60
ASCII Text
x 
 
Wolfgang Aigner, Silvia Miksch, Wolfgang Müller, Heidrun Schumann, Christian Tominski, "Visual Methods for Analyzing Time-Oriented Data," IEEE Transactions on Visualization and Computer Graphics, vol. 14, no. 1, pp. 47-60, January/February, 2008.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2007.70415,
author = {Wolfgang Aigner and Silvia Miksch and Wolfgang Müller and Heidrun Schumann and Christian Tominski},
title = {Visual Methods for Analyzing Time-Oriented Data},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {14},
number = {1},
issn = {1077-2626},
year = {2008},
pages = {47-60},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2007.70415},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - Visual Methods for Analyzing Time-Oriented Data
IS - 1
SN - 1077-2626
SP47
EP60
EPD - 47-60
A1 - Wolfgang Aigner,
A1 - Silvia Miksch,
A1 - Wolfgang Müller,
A1 - Heidrun Schumann,
A1 - Christian Tominski,
PY - 2008
KW - Time-Oriented Data
KW - Visualization
KW - Analysis
KW - User
VL - 14
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
Providing appropriate methods to facilitate the analysis of time-oriented data is a key issue in many application domains. In this paper, we focus on the unique role of the parameter time in the context of visually driven data analysis.We will discuss three major aspects — visualization, analysis, and the user. It will be illustrated that it is necessary to consider the characteristics of time when generating visual representations.For that purpose we take a look at different types of time and present visual examples. Integrating visual and analytical methods has become an increasingly important issue. Therefore, we present our experiences in temporal data abstraction, principal component analysis, and clustering of larger volumes of time-oriented data. The third main aspect we discuss is supporting user-centered visual analysis.We describe event-based visualization as a promising means to adapt the visualization pipeline to needs and tasks of users.

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Index Terms:
Time-Oriented Data, Visualization, Analysis, User
Citation:
Wolfgang Aigner, Silvia Miksch, Wolfgang Müller, Heidrun Schumann, Christian Tominski, "Visual Methods for Analyzing Time-Oriented Data," IEEE Transactions on Visualization and Computer Graphics, vol. 14, no. 1, pp. 47-60, Jan.-Feb. 2008, doi:10.1109/TVCG.2007.70415
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