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Visual analysis of large graphs

: Landesberger, Tatiana von; Kuijper, Arjan; Schreck, Tobias; Kohlhammer, Jörn; Wijk, Jarke van; Fekete, Jean-Daniel; Fellner, Dieter W.

Hauser, H. ; European Association for Computer Graphics -EUROGRAPHICS-:
Eurographics 2010. STARs - State of the Art Reports
Aire-la-Ville: Eurographics Association, 2010
European Association for Computer Graphics (Eurographics Annual Conference) <31, 2010, Norrköping>
Conference Paper
Fraunhofer IGD ()
data structures; graph; network; user interface; information system; Forschungsgruppe Visual Search and Analysis (VISA)

The analysis of large graphs plays a prominent role in various fields of research and is relevant in many important application areas. Effective visual analysis of graphs requires appropriate visual presentations in combination with respective user interaction facilities and algorithmic graph analysis methods. How to design appropriate graph analysis systems depends on many factors, including the type of graph describing the data, the analytical task at hand, and the applicability of graph analysis methods. The most recent surveys of graph visualization and navigation techniques were presented by Herman et al. [HMM00] and Diaz [DPS02]. The first work surveyed the main techniques for visualization of hierarchies and graphs in general that had been introduced until 2000. The second work concentrated on graph layouts introduced until 2002. Recently, new techniques have been developed covering a broader range of graph types, such as time-varying graphs. Also, in accordance with ever growing amounts of graph-structured data becoming available, the inclusion of algorithmic graph analysis and interaction techniques becomes increasingly important.
In this State-of-the-Art Report, we survey available techniques for the visual analysis of large graphs. Our review firstly considers graph visualization techniques according to the type of graphs supported. The visualization techniques form the basis for the presentation of interaction approaches suitable for visual graph exploration. As an important component of visual graph analysis, we discuss various graph algorithmic aspects useful for the different stages of the visual graph analysis process.