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The temporal evolution of scientific data is of high relevance in many fields of application. Understanding the dynamics over time is a crucial step in understanding the underlying system. The availability of large scale parallel computers has led to a finer and finer resolution of simulation data, which makes it difficult to detect all relevant changes of the system by watching a video or a set of snapshots. In recent years, algorithms for the automatic detection of coherent temporaldoi:10.4230/dfu.vol2.sciviz.2011.118 dblp:conf/dagstuhl/Janicke11 fatcat:2rejavgw6jbd5lauanutcutcgu