TopoInVis2022 Honorable Mention Award for „Reduced Connectivity for Local Bilinear Jacobi Sets“

At this year's IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis2022), Daniel Klötzl, Tim Krake, Youjia Zhou, Jonathan Stober, Kathrin Schulte, Ingrid Hotz, Bei Wang and Daniel Weiskopf received the Honorable Mention Award for their publication "Reduced Connectivity for Local Bilinear Jacobi Sets". The TopoInVis Workshop was held in conjunction with IEEE VIS 2022 in Oklahoma City, USA.

We present a new topological connection method for the local bilinear computation of Jacobi sets that improves the visual representation while preserving the topological structure and geometric configuration. To this end, the topological structure of the local bilinear method is utilized, which is given by the nerve complex of the traditional piecewise linear method. Since the nerve complex consists of higher-dimensional simplices, the local bilinear method (visually represented by the 1-skeleton of the nerve complex) leads to clutter via crossings of line segments. Therefore, we propose a homotopy-equivalent representation that uses different collapses and edge contractions to remove such artifacts. Our new connectivity method is easy to implement, comes with only little overhead, and results in a less cluttered representation.

• Michael Sedlmair and his team received the Ten Year Test of Time Award
• IEEE VIS 2022 Best Paper Award for "Uncertainty-Aware Multidimensional Scaling"