Improving Big Data visual analytics with interactive virtual reality

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 a virtual reality platform. After running proven analytics on the data, we intend to represent the information in a more realistic 3D setting, where analysts can achieve an enhanced situational awareness and rely on familiar perceptions to draw in-depth conclusions on the dataset. In addition, developing a human-computer interface that responds to natural user actions and inputs creates a more intuitive environment. Tasks can be performed to manipulate the dataset and allow users to dive deeper upon request, adhering to desired demands and intentions. Due to the volume and popularity of social media, we developed a 3D tool visualizing Twitter on MIT's campus for analysis. Utilizing emerging technologies of today to create a fully immersive tool that promotes visualization and interaction can help ease the process of understanding and representing big data.

The affordance of virtual reality to enable the sensory representation of multi-dimensional data for immersive analytics: from experience to insight

“…there has been a renewal of interest in the potential of VR to enhance VDM. Our review of this 'VR 2.0' activity includes: a range of experiments using abstract visualization of data within collaborative worlds [23]; a position paper on embodied interaction and perception [24]; a case study on visualizing social media data [25]; a comprehensive overview and discussion of the challenges for data visualization [26]; a position paper and application for aerospace [27]; and the establishment of a network of researchers articulating immersive analytics as a specialist new field of research [28]. The premise behind the renewed interest in the higher spatial, graphic and aural fidelity afforded by VR is that the "more dimensions we can visualize effectively, the higher are our chances of recognizing potentially interesting patterns, correlations, or outliers" [23].…”

Exploring DrugBank in Virtual Reality Chemical Space

“…After the introduction of VR support in popular 3D engines supporting VR like Unity and Unreal, multiple groups have successfully implemented VR representations of scientific data. [23][24][25][26][27][28] Here we present an extension of our previous work on interactive visualizations of chemical spaces to VR. As with our previously released tools, the application allows for the seamless navigation between global and local features of large data sets, enabling an intuitive exploration of chemical spaces.…”

A Virtual Reality Approach for Exploring Spatio-Temporal Urban Data

“…Some initial efforts to implement immersive representations of movement data, such as the STC, have been reported by Theuns [9], using a VR HMD-based prototype, and Saenz et al [10], using an Augmented Reality (AR) HMD. Moran et al [11] also explored a VR approach for the visualization of geo-tagged Twitter posts originated from the MIT campus. Tweets were distributed in a virtual recreation of the campus, and the particular representation of each was determined by its content.…”