The qualitative analysis of nonverbal communication is more and more relying on 3D recording technology. However, the human analysis of 3D data on a regular 2D screen can be challenging as 3D scenes are difficult to visually parse. To optimally exploit the full depth of the 3D data, we propose to enhance the 3D view with a number of visualizations that clarify spatial and conceptual relationships and add derived data like speed and angles. In this paper, we present visualizations for directional body motion, hand movement direction, gesture space location, and proxemic dimensions like interpersonal distance, movement and orientation. The proposed visualizations are available in the open source tool JMocap and are planned to be fully integrated into the ANVIL video annotation tool. The described techniques are intended to make annotation more efficient and reliable and may allow the discovery of entirely new phenomena.