Immersive analytics is an emerging field of data exploration and analysis in immersive environments. It is an active research area that explores human-centric approaches to data exploration and analysis based on the spatial arrangement and visualization of data elements in immersive 3D environments. The availability of immersive extended reality systems has increased tremendously recently, but it is still not as widely used as conventional 2D displays. In this dissertation, we described an immersive analysis system for spatiotemporal data and performed several user studies to measure the user performance in the developed system, and laid out design guidelines for an immersive analytics environment. In our first study, we compared the performance of users based on specific visual analytics tasks in an immersive environment and on a conventional 2D display. The approach was realized based on the coordinated multiple-views paradigm. We also designed an embodied interaction for the exploration of spatial time series data. The findings from the first user study showed that the developed system is more efficient in a real immersive environment than using it on a conventional 2D display. One of the important challenges we realized while designing an immersive analytics environment was to find the optimal placement and identification of various visual elements. In our second study, we explored the iterative design of the placement of visual elements and interaction with them based on frames of reference. Our iterative designs explored the impact of the visualization scale for three frames of reference and used the collected user feedback to compare the advantages and limitations of these three frames of reference. In our third study, we described an experiment that quantitatively and qualitatively investigated the use of sonification, i.e., conveying information through nonspeech audio, in an immersive environment that utilized empirical datasets obtained from a multi-dimensional geophysical system. We discovered that using event-based sonification in addition to the visual channel was extremely effective in identifying patterns and relationships in large, complex datasets. Our findings also imply that the inclusion of audio in an immersive analytics system may increase users’ level of confidence when performing analytics tasks like pattern recognition. We outlined the sound design principles for an immersive analytics environment using real-world geospace science datasets and assessed the benefits and drawbacks of using sonification in an immersive analytics setting. / Doctor of Philosophy / When it comes to exploring data, visualization is the norm. We make line charts, scatter plots, bar graphs, or heat maps to look for patterns in data using traditional desktop-based approaches. However, biologically humans are optimized to observe the world in three dimensions. This research is motivated by the idea that representing data in immersive 3D environments can provide a new perspective that may lead to the discovery of previously undetected data patterns. Experiencing the data in three dimensions, engaging multiple senses like sound and sight, and leveraging human embodiment, interaction capabilities, and sense of presence may lead to a unique understanding of the data that is not feasible using traditional visual analytics. In this research, we first compared the data analysis process in a mixed reality system, where real and virtual worlds co-exist, versus doing the same analytical tasks in a desktop-based environment. In our second study, we studied where different charts and data visualizations should be placed based on the scale of the environment, such as table-top versus room-sized. We studied the strengths and limitations of different scales based on the visual and interaction design of the developed system. In our third study, we used a real-world space science dataset to test the liabilities and advantages of using the immersive approach. We also used audio and explored what kinds of audio work for which analytical tasks and laid out design guidelines based on audio. Through this research, we studied how to do data analytics in emerging mixed reality environments and presented results and design guidelines for future developers, designers, and researchers in this field.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/115343 |
| Date | 05 June 2023 |
| Creators | Sardana, Disha |
| Contributors | Graduate School, Bukvic, Ivica, Earle, Gregory D., Gracanin, Denis, Jeon, Myounghoon |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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