Improving Big Data Visual Analytics with Interactive Virtual Reality
Andrew Moran, Vijay Gadepally, Matthew Hubbell, Jeremy Kepner

TL;DR
This paper proposes an immersive virtual reality platform for big data visual analytics, combining geospatial visualization and natural interaction to enhance understanding and analysis of large datasets.
Contribution
It introduces a novel VR-based visualization and interaction approach specifically designed for big data analysis, focusing on geospatial data and social media integration.
Findings
Enhanced situational awareness in 3D VR environment
Improved user interaction with natural inputs
Effective visualization of Twitter data on campus
Abstract
For decades, the growth and volume of digital data collection has made it challenging to digest large volumes of information and extract underlying structure. Coined 'Big Data', massive amounts of information has quite often been gathered inconsistently (e.g from many sources, of various forms, at different rates, etc.). These factors impede the practices of not only processing data, but also analyzing and displaying it in an efficient manner to the user. Many efforts have been completed in the data mining and visual analytics community to create effective ways to further improve analysis and achieve the knowledge desired for better understanding. Our approach for improved big data visual analytics is two-fold, focusing on both visualization and interaction. Given geo-tagged information, we are exploring the benefits of visualizing datasets in the original geospatial domain by utilizing…
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