  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.
