HoNVis is a visualization and interactive exploration software for higher-order networks.
Unlike the conventional first-order network (FoN), the higher-order network (HoN) provides a more accurate description of transitions by creating additional nodes to encode higher-order dependencies. However, there exists no visualization and exploration tool for the HoN. For applications such as the development of strategies to control species invasion through global shipping which is known to exhibit higher-order dependencies, the existing FoN visualization tools are limited. In this paper, we present HoNVis, a novel visual analytics framework for exploring higher-order dependencies of the global ocean shipping network. Our framework leverages coordinated multiple views to reveal the network structure at three levels of detail (i.e., the global, local, and individual port levels). Users can quickly identify ports of interest at the global level and specify a port to investigate its higher-order nodes at the individual port level. Investigating a larger-scale impact is enabled through the exploration of HoN at the local level. Using the global ocean shipping network data, we demonstrate the effectiveness of our approach with a real-world use case conducted by domain experts specializing in species invasion. Finally, we discuss the generalizability of this framework to other real-world applications such as information diffusion in social networks and epidemic spreading through air transportation.
HoNVis extends HON’s value to real-world practices. Previously, there was no tool to handle the rich information and complex dependencies in HON, which was a major obstacle to pattern discovery and interpretation. The software package I collaborated on is the first to make it possible to interactively explore HON and support real-world decisions. On the right is a screenshot of the global shipping network represented as HON in our visualization software. Users can import heterogeneous data, quickly identify interactive patterns of interest, explore at different granularities, trace propagation pathways and see how they expand the subgraph of ports invaded by certain species, test targeted species control strategies for given ports / shipping routes, and drill down to the raw data to understand the formation and evolution of higher-order dependencies. This software package expedites the discovery of complex patterns and facilitates real-world applications in targeted control and decision making.