An Overview of Immersive Data Visualisation Methods Using Type by Task Taxonomy

Abstract

The use of virtual reality (VR) technology in data visualisation and analytics introduces a new way for users to explore and understand the data through Immersive Analytics (IA). However, previous works evaluated the IA based on the traditional 2D visualisation tasks and thus reduced the VR benefits. The IA is also still in its infancy and lacks standard design guidelines for user tasks and evaluation. Hence, this paper aims to review the information exploration tasks in IA. This work used the systematic literature review methodology to search and analyse the literature, where there were eighteen studies identified for the systematic mapping based on type by task taxonomy. The timestep task is an additional user task proposed to support the IA function. The studies found that the IA supports various data visualisation fields and spatial tasks. Lastly, the limitation of this paper is discussed to identify potential future studies.