Dear All,
we submitted the paper /dg2pix: Pixel-Based Visual Analysis of Dynamic
Graphs/ to the Visualization in Data Science (VDS at IEEE VIS 2020). We
request to acknowledge SPARTA if the paper is accepted.
* 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 explore the evolving data at different
temporal aggregation scales simultaneously. 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 easily identified and interpreted over time. Our dg2pix
contributes a suitable intermediate representation between node-link
diagrams at the high detail end, and matrix representations on the
low detail end."
Best Regards,
Eren Cakmak
--
Research Associate
Department of Computer and Information Science
Data Analysis and Visualization Group
78457 Konstanz, Germany
Website:
http://infovis.uni.kn/~cakmak
Phone: +49 (0)7531 88 2507
Room: D334