Visualization in virtual reality: a systematic review

TL;DR

This systematic review analyzes current research on visualization in virtual reality, highlighting the use of game engines, the lack of standard guidelines, and the prevalence of traditional 3D statistical visualizations in VR.

Contribution

It provides a comprehensive overview of the state-of-the-art in VR visualization research, identifying gaps and future directions in guidelines and evaluation methods.

Findings

Few studies focus on standard VR guidelines.

Game engines are widely used but have limitations for scientific research.

Traditional 3D statistical visualizations remain common in VR.

Abstract

Rapidly growing virtual reality (VR) technologies and techniques have gained importance over the past few years, and academics and practitioners have been searching for efficient visualizations in VR. To date, emphasis has been on the employment of game technologies. Despite the growing interest and discussion, visualization studies have lacked a common baseline in the transition period of 2D visualizations to immersive ones. To this end, the presented study aims to provide a systematic literature review that explains the state-of-the-art research and future trends on visualization in virtual reality. The research framework is grounded in empirical and theoretical works of visualization. We characterize the reviewed literature based on three dimensions: (a) Connection with visualization background and theory, (b) Evaluation and design considerations for virtual reality visualization, and (c) Empirical studies. The results from this systematic review suggest that: (1) There are only a few studies that focus on creating standard guidelines for virtual reality, and each study individually provides a framework or employs previous studies on traditional 2D visualizations; (2) With the myriad of advantages provided for visualization and virtual reality, most of the studies prefer to use game engines; (3) Although game engines are extensively used, they are not convenient for critical scientific studies; and (4) 3D versions of traditional statistical visualization techniques, such as bar plots and scatter plots, are still commonly used in the data visualization context. This systematic review attempts to add to the literature a clear picture of the emerging contexts, different elements, and their interdependencies.