In the past three years, the so-called second wave of Virtual Reality (VR) has brought us a vast amount of new displays and input devices. Not only new hardware has entered the consumer market providing affordable pricing models but also completely new technologies are being designed and developed. Additionally new concepts for handling existing problems on the hardware and software side of the VR technology are constantly being introduced. This software and hardware development is mainly lead by enthusiasts interested in the domain of VR opposed to the established scientific community, which already partially makes use of the newly available technology. Besides Head-Mounted Displays (HMDs), either cable-based or mobile, other devices like haptics devices, controllers, vests, omnidirectional treadmills, tracking technologies, as well as optical scanners for gesture-based interaction are gaining importance in the field of commodity VR. Most of these technologies are already precise and robust enough to be used for professional operation and scientific experiments. The topics discussed are the common issues with the new technologies including the approaches to solve them as for example motion-to-photon latency, barrel distortion, and low-persistence displays. Additionally an in-depth analysis of the available solutions expected to hit the market is provided. A taxonomy categorising the current developments with the chosen implementation approaches will be given. The paper analyses the state of technological advancements in the field and provides an extensive overview on the current development considering the upcoming devices and the advancements from the software side.

Although virtual reality (VR) has a huge success in increasing the quality of scientific visualization applications, there is a considerable lag in the development of VR applications in the case of information visualization (InfoVis). Some researchers in InfoVis claim that 2D representations are enough for data analysis; however, in the case of multi-dimensional datasets, other researchers indicate that studying multiple dimensions simultaneously is advantageous [1], [2], [3]. The first studies with low quality stereoscopic devices showed no advantages when performing simple tasks on simple datasets [4]. However, recent experiments using higher quality devices and more complex datasets show a huge improvement in performance [5]. Still, designing an effective 3D representation remains a complex endeavour. Brath [6] provides a list of things to take into account. This paper shows how a CAVE-like2 environment can allow the study of multi-dimensional datasets while keeping multiple 2D representations available, using genome comparisons as a usecase. Parallel coordinate plots and non-planar graph representation in 3D space are also described. Some potential applications in aerospace are also listed (this is by no means a complete listing of applications; readers are encouraged to suggest new ones).