Current State of the Art and Future Directions: Augmented Reality Data Visualization To Support Decision-Making
Mengya Zheng, David Lillis and Abraham G. Campbell
Visual Informatics, 2024.
Abstract
Augmented Reality (AR), as a novel data visualization tool, is advantageous in revealing spatial data patterns and data-context associations. Accordingly, recent research has identified AR data visualization as a promising approach to increasing decision-making efficiency and effectiveness. As a result, AR has been applied in various decision support systems to enhance knowledge conveying and comprehension, in which the different data-reality associations have been constructed to aid decision-making. However, how these AR visualization strategies can enhance different decision support datasets has not been reviewed thoroughly. Especially given the rise of Big Data in the modern world, this support is critical to decision-making in the coming years. Using AR to embed the decision support data and explanation data into the end user's physical surroundings and focal contexts avoids isolating the human decision-maker from the relevant data. Integrating the decision-maker's contexts and the DSS support in AR is a difficult challenge. This paper outlines the current state of the Art through a literature review in allowing AR data visualization to support decision-making. To facilitate the publication classification and analysis, the paper proposes one taxonomy to classify different AR data visualization based on the semantic associations between the AR data and physical context. Based on this taxonomy and a decision support system taxonomy, 37 publications have been classified and analyzed from multiple aspects. One of the contributions of this literature review is a resulting AR visualization taxonomy that can be applied to decision support systems. Along with this novel tool, the paper discusses the current state of Art in this field and indicates possible future challenges and directions that AR Data Visualization will bring to support decision-making.