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Interactive visual comparison of multiple trees

: Bremm, Sebastian; Landesberger, Tatiana von; Heß, Martin; Schreck, Tobias; Weil, Phillip; Hamacher, Kay


Miksch, S. ; IEEE Computer Society, Technical Committee on Visualization and Graphics:
IEEE Conference on Visual Analytics Science and Technology, VAST 2011. Proceedings : 23-28 October 2011, Providence, Rhode Island, USA
New York, NY: IEEE, 2011
ISBN: 978-1-4673-0013-1
ISBN: 978-1-4673-0015-5 (Print)
Conference on Visual Analytics Science and Technology (VAST) <6, 2011, Providence/RI>
Conference Paper
Fraunhofer IGD ()
comparison; visualization; visual analytic; Forschungsgruppe Visual Search and Analysis (VISA)

Traditionally, the visual analysis of hierarchies, respectively, trees, is conducted by focusing on one given hierarchy. However, in many research areas multiple, differing hierarchies need to be analyzed simultaneously in a comparative way - in particular to highlight differences between them, which sometimes can be subtle. A prominent example is the analysis of so-called phylogenetic trees in biology, reflecting hierarchical evolutionary relationships among a set of organisms. Typically, the analysis considers multiple phylogenetic trees, either to account for statistical significance or for differences in derivation of such evolutionary hierarchies; for example, based on different input data, such as the 16S ribosomal RNA and protein sequences of highly conserved enzymes. The simultaneous analysis of a collection of such trees leads to more insight into the evolutionary process.
We introduce a novel visual analytics approach for the comparison of multiple hierarchies focusing on both global and local structures. A new tree comparison score has been elaborated for the identification of interesting patterns. We developed a set of linked hierarchy views showing the results of automatic tree comparison on various levels of details. This combined approach offers detailed assessment of local and global tree similarities. The approach was developed in close cooperation with experts from the evolutionary biology domain. We apply it to a phylogenetic data set on bacterial ancestry, demonstrating its application benefit.