Heterogeneous networks and multi-level networks occur in several application fields where their integration, combination, comparison, analysis, and visualization poses major challenges. In this chapter, we analyze the general characteristics of this type of data and identify examples in three application domains: biology, social sciences, and software engineering. Conceptually, we focus on sets of multivariate networks at two or more levels. Each level may describe a specific scale, and within each level several related heterogeneous networks are represented. We allow n:m mappings within the same level, but only 1:n mappings across levels that must be consecutive. This leads to a structured data set that is the basis for further visual analysis. Our chapter ends with ideas to visualize those networks together with the relationships between them and highlights research challenges.