dg2pix : Pixel-Based Visual Analysis of Dynamic Graphs
dg2pix : Pixel-Based Visual Analysis of Dynamic Graphs
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2020
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Proceedings of IEEE Visualization in Data Science (VDS). - Piscataway, NJ : IEEE, 2020. - pp. 32-41. - ISBN 978-1-72819-284-0
Abstract
Presenting long sequences of dynamic graphs remains challenging due to the underlying large-scale and high-dimensional data. We propose dg2pix, a novel pixel-based visualization technique, to visually explore temporal and structural properties in long sequences of large-scale graphs. The approach consists of three main steps: (1) the multiscale modeling of the temporal dimension; (2) unsupervised graph embeddings to learn low-dimensional representations of the dynamic graph data; and (3) an interactive pixel-based visualization to simultaneously explore the evolving data at different temporal aggregation scales. dg2pix provides a scalable overview of a dynamic graph, supports the exploration of long sequences of high-dimensional graph data, and enables the identification and comparison of similar temporal states. We show the applicability of the technique to synthetic and real-world datasets, demonstrating that temporal patterns in dynamic graphs can be identified and interpreted over time. dg2pix contributes a suitable intermediate representation between node-link diagrams at the high detail end and matrix representations on the low detail end.
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004 Computer Science
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IEEE Visualization in Data Science (VDS) (Virtual Conference), Oct 26, 2020, Salt Lake City, Utah
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CAKMAK, Eren, Dominik JÄCKLE, Tobias SCHRECK, Daniel A. KEIM, 2020. dg2pix : Pixel-Based Visual Analysis of Dynamic Graphs. IEEE Visualization in Data Science (VDS) (Virtual Conference). Salt Lake City, Utah, Oct 26, 2020. In: Proceedings of IEEE Visualization in Data Science (VDS). Piscataway, NJ:IEEE, pp. 32-41. ISBN 978-1-72819-284-0. Available under: doi: 10.1109/VDS51726.2020.00008BibTex
@inproceedings{Cakmak2020dg2pi-51036, year={2020}, doi={10.1109/VDS51726.2020.00008}, title={dg2pix : Pixel-Based Visual Analysis of Dynamic Graphs}, isbn={978-1-72819-284-0}, publisher={IEEE}, address={Piscataway, NJ}, booktitle={Proceedings of IEEE Visualization in Data Science (VDS)}, pages={32--41}, author={Cakmak, Eren and Jäckle, Dominik and Schreck, Tobias and Keim, Daniel A.} }
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