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