  Surgical simulators not only allow planning and training of complex
procedures, but also offer the ability to generate structured data for
algorithm development, which may be applied in image-guided computer assisted
interventions. While there have been efforts on either developing training
platforms for surgeons or data generation engines, these two features, to our
knowledge, have not been offered together. We present our developments of a
cost-effective and synergistic framework, named Asynchronous Multibody
Framework Plus (AMBF+), which generates data for downstream algorithm
development simultaneously with users practicing their surgical skills. AMBF+
offers stereoscopic display on a virtual reality (VR) device and haptic
feedback for immersive surgical simulation. It can also generate diverse data
such as object poses and segmentation maps. AMBF+ is designed with a flexible
plugin setup which allows for unobtrusive extension for simulation of different
surgical procedures. We show one use case of AMBF+ as a virtual drilling
simulator for lateral skull-base surgery, where users can actively modify the
patient anatomy using a virtual surgical drill. We further demonstrate how the
data generated can be used for validating and training downstream computer
vision algorithms
