MultiVis: A Visual-Analysis Method for Multilayer Network

Multilayer networks are widely adopted as flexible models for characterizing complex systems with diverse interconnection types. Nevertheless, mainstream existing visualization tools are predominantly designed for single-layer network scenarios, and limited functional support is provided for inter-layer comparative analysis. In this work, MultiVis is proposed as a dedicated visual-analysis framework for multilayer networks, which couples topological structure visualization with high-order information pattern representation. Within the topological view, network compression, community detection, and multiple layout algorithms are integrated to uncover multi-scale (macro, meso, and micro) structural features of networks at intra-layer and inter-layer levels. In the high-order pattern view, area-proportional Venn diagrams are utilized to quantify the overlapping sets of nodes and edges across layers, while directed arrow diagrams are adopted to visualize intricate inter-community interaction patterns. A multi-view interaction pipeline derived from the Card reference model is constructed to support user-driven data abstraction, visual encoding, and cross-view transformation. All the aforementioned visual modules and multidirectional interactive operations are implemented in a browser-based prototype named MultiVisSys. User-study results from thirteen participants demonstrate that the developed system delivers satisfactory usability for inter-layer similarity comparison, while its objective analytical performance remains to be further verified through large-scale empirical evaluations.