Visual Analysis of Large Graphs: State‐of‐the‐Art and Future Research Challenges

By T. V. Landesberger, Arjan Kuijper, Tobias Schreck, Jörn Kohlhammer, Jack van Wijk, Jean-Daniel Fekete, D. Fellner. Eurographics, 2011

597 citations recorded by the source corpus.

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 cover techniques that had been introduced until 2000 or concentrate only on graph layouts published 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 first 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. We also present main open research challenges in this field.

Subfields: Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/eee930533b539d872d7777aa6e7fa767b1fa6822

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In Computer Vision and Pattern Recognition

1. Shixia Liu
2. Mengchen Liu
3. Yingcai Wu
4. Weiwei Cui
5. Ronghua Liang
6. Guodao Sun
7. Paul Vickers
8. Helen Gibson

In Statistical and Nonlinear Physics

1. Shixia Liu
2. Mengchen Liu
3. Yingcai Wu
4. Weiwei Cui
5. Paul Vickers
6. Helen Gibson
7. Martin J Lercher
8. Joe Faith

In Signal Processing

1. Yingcai Wu
2. Paul Vickers
3. Mengchen Liu
4. Helen Gibson
5. Weiwei Cui
6. Joe Faith
7. Ronghua Liang
8. Guodao Sun

Citations in the corpus

• A survey of two-dimensional graph layout techniques for information visualisation (2013, methodology): “Finally, it has also been suggested that interaction, or at least user involvement, in the layout process, as found with MagnetViz and TPP, is a promising approach to creating new layouts.(141) This review has presented some of the most commonly used and implemented techniques for graph layout in in”
• A Survey of Visual Analytics Techniques and Applications: State-of-the-Art Research and Future Challenges (2013, background): “Keywords visual analytics, information visualization, data analysis, user interaction”
• A survey on information visualization: recent advances and challenges (2014, background): “Existing surveys were either conducted several years ago [47,143] or focus on a specific topic of visualization such as graph visualization [145], software visualization [24], or visualization of network security events [124].”
• Evolview v3: a webserver for visualization, annotation, and management of phylogenetic trees (2019, background): “(4) Search box, allowing the user to search across projects and trees.”