Data visualisation in a virtual environment (VE) opens up new ways of presenting data and makes it possible for the observer to explore data in an immersive way. However, it also comes with a number of challenges. One of these challenges is data distinguishability. The data needs to be distinguishable against the background, but in a VE where the user can move around and observe the data from different perspectives, the backdrop will be constantly changing. This thesis studies this challenge and contributes knowledge to current research about data visualisation in VEs. The research question When in a detailed virtual environment, what impact does the varying background have on distinguishability of visualised data? is answered using a digital self -completion questionnaire and four hypotheses.  The data were not able to clearly determine if one of the colourmap used (YellowRed, Rainbow) was overall more effective than the other one. However, the rainbow colourmap did have marginally better results and was chosen by more participants as their preferred colourmap. The results did show that a larger number of participants disagreed that the light background made the data easier to distinguish in comparison to a dark backdrop. The results showed that more participants found it easier to see the data when seen from above than when from below. The two colourmaps were not equally effective regarding how well they could show both the VE and the data: The results indicating that the YellowRed colourmap was better at showing the details of the VE but not as good at distinguishing the data, whilst the Rainbow colourmap had the reverse results being better at distinguishing the data but less effective at showing the background.  The thesis concludes that it has fulfilled its goal of establishing a starting point for further studies, further studies that, according to the author, is woefully needed.