Immersive Insights: A Hybrid Analytics System for Collaborative Exploratory Data Analysis
This work addresses the need for quantifying the benefits of immersive technologies in data science workflows, but appears incremental as it builds on existing research in AR/VR for data tasks.
The paper tackled the problem of understanding how augmented reality (AR) and virtual reality (VR) technologies impact exploratory data analysis (EDA) in collaborative settings, and found that their hybrid system, Immersive Insights, was evaluated in a user study with twelve data scientists to compare performance against a state-of-the-art non-immersive system.
In the past few years, augmented reality (AR) and virtual reality (VR) technologies have experienced terrific improvements in both accessibility and hardware capabilities, encouraging the application of these devices across various domains. While researchers have demonstrated the possible advantages of AR and VR for certain data science tasks, it is still unclear how these technologies would perform in the context of exploratory data analysis (EDA) at large. In particular, we believe it is important to better understand which level of immersion EDA would concretely benefit from, and to quantify the contribution of AR and VR with respect to standard analysis workflows. In this work, we leverage a Dataspace reconfigurable hybrid reality environment to study how data scientists might perform EDA in a co-located, collaborative context. Specifically, we propose the design and implementation of Immersive Insights, a hybrid analytics system combining high-resolution displays, table projections, and augmented reality (AR) visualizations of the data. We conducted a two-part user study with twelve data scientists, in which we evaluated how different levels of data immersion affect the EDA process and compared the performance of Immersive Insights with a state-of-the-art, non-immersive data analysis system.