Abstract. Interaction is a vital component in the visualization of multivariate networks. It enables greater amounts of information to be seen and explored than is possible with static visualization. Interaction can also help show the information landscape of the data while still allowing users to find and view areas of interest in greater detail and pivot between these. In this chapter we first discuss the design space and requirements for interacting with large multivariate data sets. We describe and classify relevant interaction techniques, and give examples of the interactive aspects of multivariate graph visualization systems. We present recommendations and guidelines for designing novel interaction approaches. Finally, we describe the open challenges within the field of multivariate graph visualization as we see them.