Virtual reality (VR) is a medium of human interaction which is becoming more popular by the day in today's technological advancements. The applications are being developed at the same rate as the technology itself and we have only seen the start of the possible benefits it could bring society. As the technology advances it will gain a lot of trust, and the potential use cases of virtual environments will be allowed to become more complex. Already today, they often involve network streaming components which often has very strict optimization requirements in order to be able to run in real-time with minimal delay under normal network conditions. In order to reach the required optimizations it is important to understand how users interact with such virtual environments. To support and facilitate the understanding of this kind of interaction we have developed a method for creating qualitative datasets containing extensive information about the 3D scene as well as the sensor data from the head-mounted display (HMD). We then apply this method to create a sample dataset from a virtual 3D environment and try to analyze the data collected through some simple methods for demonstrational purposes.