Humans spend most of their life in indoor spaces. As indoor spaces are becoming increasingly complex, there are compelling needs for efficient indoor GIS and navigation systems. For indoor navigations, numerous geometric network models have been proposed as navigable spatial models for 3D indoor environments in the past decade. Most of the existing discussions, however, tend to focus on conceptual representations of geometric networks; not enough attention has been given on the generation processes of navigable networks for 3D indoor environments. It is actually nontrivial, considering accurate and complete floor plans, the conventional data sources for building indoor geometric networks, are oftentimes not available for various reasons (e.g., copyright, public safety concerns). With the continue advances of 3D imaging and scanning technologies, 3D data models with fine geometric structures and high quality textures are increasingly available for indoor spaces, thus provide a novel data source for building indoor geometric networks. In this paper, an interactive approach is presented to derive 3D, navigable, geometric network models from these 3D data models. Specifically, this approach includes three steps: decomposing 3D building models in terms of floors, interactively creating geometric network elements (e.g., nodes and edges) and then automatically generating geometric network models. The presented approach is implemented and its advantages are demonstrated with a real world 3D building data.