Higher-order network modeling and analysis are vital to understanding the structures governing the configuration and behavior of complex networks. While network motifs are known to be fundamental building blocks of complex networks, the higher-order configuration and organization of complex networks remain widely unknown. In this work, we develop interactive visual higher-order network mining and modeling techniques to gain insight into the higher-order structure and composition of complex networks. The approach uncovers higher-order configurations including important phenotypes in a human gene interaction network and hubs in a power grid network.