Database Reference
In-Depth Information
Visual Analytics:
Definition, Process, and Challenges
Daniel Keim 1 , Gennady Andrienko 2 , Jean-Daniel Fekete 3 ,CarstenGorg 4 ,
Jorn Kohlhammer 5 ,andGuyMelancon 6
1 Department of Computer and Information Science, University of Konstanz,
78457 Konstanz, Germany,
keim@informatik.uni-konstanz.de
2 Fraunhofer Institute for Intelligent Analysis and Information Systems(IAIS),
Schloss Birlinghoven 53754 Sankt Augustin, Germany,
gennady.andrienko@iais.fraunhofer.de
3 Universite Paris-Sud, INRIA, Bat 490,
F-91405 Orsay Cedex, France,
Jean-Daniel.Fekete@inria.fr
4 School of Interactive Computing & GVU Center, Georgia Institute of Technology,
85 5th St., NW, Atlanta, GA 30332-0760, USA,
goerg@cc.gatech.edu
5 Fraunhofer Institute for Computer Graphics Research,
Fraunhoferstraße 5, D-64283 Darmstadt, Germany,
joern.kohlhammer@igd.fraunhofer.de
6 INRIA Bordeaux - Sud-Ouest, CNRS UMR 5800 LaBRI,
Campus Universite Bordeaux I,
351 Cours de la liberation, 33405 Talence Cedex, France,
Guy.Melancon@labri.fr
1
Introduction and Motivation
We are living in a world which faces a rapidly increasing amount of data to be
dealt with on a daily basis. In the last decade, the steady improvement of data
storage devices and means to create and collect data along the way influenced our
way of dealing with information: Most of the time, data is stored without filtering
and refinement for later use. Virtually every branch of industry or business,
and any political or personal activity nowadays generate vast amounts of data.
Making matters worse, the possibilities to collect and store data increase at a
faster rate than our ability to use it for making decisions. However, in most
applications, raw data has no value in itself; instead we want to extract the
information contained in it.
The information overload problem refers to the danger of getting lost in
data which may be
- irrelevant to the current task at hand
- processed in an inappropriate way
- presented in an inappropriate way
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