Towards Visual Analytics in Virtual Environments
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Virtual reality (VR) is poised to become the new medium through which we engage, view, and consume content. In contrast to traditional 2D desktop displays, which restrict our interaction space onto an arbitrary 2D-plane with unnatural interaction mechanisms, VR expands the visualization and interaction space into our 3D domain, enabling natural observations and interactions with information. With the rise of Big Data, processing and visualizing such enormous datasets is of utmost importance and remains a difficult challenge. Machine learning, specifically deep learning, is rising to meet this challenge. In this work, we present several studies: (a) demonstrating the effectiveness of immersive environments over traditional desktops for memory recall, (b) quantifying cybersickness in virtual environments, (c) enabling human analysts and deep learning to support, refine, and enhance each other through visualization, and (d) visualizing root-DNS information, enabling analysts to find new and interesting anomalies and patterns. In our first work, we conduct a user study where participants memorize and recall a series of spatially-distributed faces on both a desktop and head-mounted display (HMD). We found that the use of virtual memory palaces in the HMD condition improves recall accuracy when compared to the traditional desktop condition. This improvement was statistically significant. Next, we present our work on quantifying cybersickness through EEG analysis. We found statistically significant correlations with increases in delta, theta, and alpha brain waves with self-reported sickness levels, enabling future virtual reality developers to design countermeasures. Third, we present our work on enabling domain experts to discover hidden labels and communities within unlabeled (or coarsely labeled) high-dimensional datasets using deep learning with visualization. Lastly, we present a 3D visualization of root-DNS traffic, revealing characteristics of a DDOS attack and changes in the distribution of queries received over time. Together, this work takes the first steps in bringing together machine learning, visual analytics, and virtual reality.