Answering why and when? A systematic literature review of application scenarios and evaluation for immersive data visualization analytics.

Abstract

Immersive analytics (IA) is a fast-growing research field that concerns improving and facilitating human sense making and data understanding through an immersive experience. Understanding the suitable application scenario that will benefit from IA enables a shift towards developing effective and meaningful applications. This paper aims to explore tasks and scenarios that can benefit from IA by conducting a systematic review of existing studies and mapping them according to the multi-level typology for abstract visualization tasks, which is also known as the what-why-how framework. The study synthesizes several works to answer the why within the context of multiple levels of specificity. In addition, this study also explores the application domains and IA guiding scenarios to address when scenarios best integrate with IA. Then, the paper discusses the IA evaluation types and research methods to evaluate an IA application that can promote effective user engagement in IA. Finally, the limitations and potential future works are discussed.