C
Carsten Görg
Researcher at University of Colorado Boulder
Publications - 57
Citations - 3528
Carsten Görg is an academic researcher from University of Colorado Boulder. The author has contributed to research in topics: Visual analytics & Information visualization. The author has an hindex of 24, co-authored 53 publications receiving 3267 citations. Previous affiliations of Carsten Görg include Saarland University & Georgia Institute of Technology.
Papers
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Book ChapterDOI
Visual Analytics: Definition, Process, and Challenges
Daniel A. Keim,Gennady Andrienko,Jean-Daniel Fekete,Carsten Görg,Jörn Kohlhammer,Guy Melançon +5 more
TL;DR: The possibilities to collect and store data increase at a faster rate than the ability to use it for making decisions, and in most applications, raw data has no value in itself; instead the authors want to extract the information contained in it.
Journal ArticleDOI
Jigsaw: supporting investigative analysis through interactive visualization
TL;DR: Jigsaw is a visual analytic system that represents documents and their entities visually in order to help analysts examine them more efficiently and develop theories about potential actions more quickly.
Proceedings ArticleDOI
Jigsaw: Supporting Investigative Analysis through Interactive Visualization
TL;DR: Jigsaw is a visual analytic system that represents documents and their entities visually in order to help analysts examine reports more efficiently and develop theories about potential actions more quickly.
Book ChapterDOI
Graphs, They Are Changing
Stephan Diehl,Carsten Görg +1 more
TL;DR: A generic algorithm for drawing sequences of graphs that considers all graphs in the sequence (offline) instead of just the previous ones (online) when computing the layout for each graph of the sequence.
Book ChapterDOI
How important is the Mental map?: an empirical investigation of a dynamic graph layout algorithm
TL;DR: This paper presents the first empirical analysis of a dynamic graph layout algorithm, focusing on the assumption that maintaining the "mental map" between time-slices assists with the comprehension of the evolving graph.