The development of crowd intelligence makes the structure of social network more complex and changeable. Research on social network should be more in-depth and focus on the changes of structure. Ego-network, which represents the relationship between specific individual and the related people, is a hot issue among the research of dynamic social network. The evolution of ego-network is highly dynamic and pluralistic, it is hard to capture its evolutionary pattern over time. To help users analyze the individual characteristics and hidden patterns in multivariate ego-network, we present EgoVis, an interactive visual analysis system for exploring and analyzing complex structural relationships in dynamic network. Based on the task requirements of network evolution analysis, we propose a task taxonomy which is suitable for ego-network research and analysis, design novel visual fonts, and analyze the evolution of dynamic ego-network relations from the three dimensions: overview, subgroup, and detail-ego. Finally, the validity and practicability of EgoVis are verified on DBLP citation network dataset.