J
Jean-Daniel Fekete
Researcher at French Institute for Research in Computer Science and Automation
Publications - 199
Citations - 11127
Jean-Daniel Fekete is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Visualization & Information visualization. The author has an hindex of 48, co-authored 185 publications receiving 10027 citations. Previous affiliations of Jean-Daniel Fekete include University of Maryland, College Park & University of Paris-Sud.
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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
NodeTrix: a Hybrid Visualization of Social Networks
TL;DR: NodeTrix is presented, a hybrid representation for networks that combines the advantages of two traditional representations: node-link diagrams are used to show the global structure of a network, while arbitrary portions of the network can be shown as adjacency matrices to better support the analysis of communities.
Journal ArticleDOI
Visual analysis of large graphs : state-of-the-art and future research challenges
T. von Landesberger,Arjan Kuijper,Arjan Kuijper,Tobias Schreck,Jörn Kohlhammer,J.J. van Wijk,Jean-Daniel Fekete,Dieter W. Fellner,Dieter W. Fellner +8 more
TL;DR: This State‐of‐the‐Art Report surveys available techniques for the visual analysis of large graphs and discusses various graph algorithmic aspects useful for the different stages of the visual graph analysis process.
Journal ArticleDOI
Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation
TL;DR: New interactive methods to explore multidimensional data using scatterplots are presented, performed using a matrix of scatterplot that gives an overview of the possible configurations, thumbnails of the scatter plots, and support for interactive navigation in the multiddimensional space.
Proceedings ArticleDOI
Task taxonomy for graph visualization
TL;DR: A list of tasks commonly encountered while analyzing graph data is suggested and it is demonstrated how all complex tasks could be seen as a series of low-level tasks performed on those objects.