Location-based data is digital information that has a real-world location. Location-based data can be used for many purposes, such as providing additional information on real-world objects or helping a user in a specific task. Access to such data can be provided in many ways, for example, with augmented reality (AR) systems. AR techniques can help its user in various tasks and the AR data can be presented to the user in various ways, depending on the task at hand. The different visualizations that can be used are heavily dependent on the hardware platform and, thus, all technologies are not suitable for every situation. This paper studies two factors that affect the visualization of location-based data. The two factors are the environment model they use, ranging from three dimensions (3D) to no dimensions (0D) at all; and the viewpoint, whether it is a first-person or a third-person view. As a result, we define a taxonomy for visualizing location-based data, where each model–view (MV) combination is referred to using its MV number. We also present numerous case studies with different MV values.