Visual Computing

University of Konstanz
IEEE Transactions on Visualization and Computer Graphics

Target Netgrams : An Annulus-Constrained Stress Model for Radial Graph Visualization

M. Xue, Y. Wang, C. Han, J. Zhang, Z. Wang, K. Zhang, C. Hurter, J. Zhao, O. Deussen

Abstract

We present Target Netgrams as a visualization technique for radial layouts of graphs. Inspired by manually created target sociograms, we propose an annulus-constrained stress model that aims to position nodes onto the annuli between adjacent circles for indicating their radial hierarchy, while maintaining the network structure (clusters and neighborhoods) and improving readability as much as possible. This is achieved by having more space on the annuli than traditional layout techniques. By adapting stress majorization to this model, the layout is computed as a constrained least square optimization problem. Additional constraints (e.g., parent-child preservation, attribute-based clusters and structure-aware radii) are provided for exploring nodes, edges, and levels of interest. We demonstrate the effectiveness of our method through a comprehensive evaluation, a user study, and a case study.

BibTeX

@Article{Xue2022TargetNetgrams,
  author  = {Xue, Mingliang and Wang, Yunhai and Han, Chang and Zhang, Jian and Wang, Zheng and Zhang, Kaiyi and Hurter, Christophe and Zhao, Jian and Deussen, Oliver},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  title   = {Target Netgrams : An Annulus-Constrained Stress Model for Radial Graph Visualization},
  year    = {2022},
  issn    = {1077-2626},
  doi     = {10.1109/TVCG.2022.3187425},
}