Uploaded July 2026 | Updated September 2026, 6 days ago
The way we interact with data is constantly evolving. As scientific datasets grow in complexity -- spanning real-time disaster response, dynamic space weather events, and large-scale Earth observation -- traditional visualization tools often fall short. This talk makes the case that mixed reality isn't just a better screen: it's a fundamentally different way to think with data.
Drawing on three real-world case studies built in mixed reality environments, I present research-backed evidence that immersive, multimodal environments measurably improve scientific pattern recognition and analytical confidence.
In a user study with 50 participants analyzing space weather datasets, audio-visual MR conditions produced 70% more identified trends than visual-only analysis.
A parallel system for earthquake disaster response demonstrates how embodied interaction with spatiotemporal data enables faster, more intuitive situational awareness.
A third case study extends these principles to Earth observation, exploring how MR can make NASA's complex geophysical datasets more accessible and actionable for researchers and decision-makers.
Across all three domains, the same design principles emerge: spatial audio, coordinated multiple views, and human-centered interaction drive real analytical gains. Attendees will leave with concrete, research-backed takeaways on what works, what doesn't, and where immersive analytics is headed next.
Session Speaker:
- Disha Sardana, SARP Coding Mentor, NASA
This session was recorded at AWE USA 2026 - the world's leading XR + AI event series. To learn more visit: awexr.com
The way we interact with data is constantly evolving. As scientific datasets grow in complexity -- spanning real-time disaster response, dynamic space weather events, and large-scale Earth observation -- traditional visualization tools often fall short. This talk makes the case that mixed reality isn't just a better screen: it's a fundamentally different way to think with data.
Drawing on three real-world case studies built in mixed reality environments, I present research-backed evidence that immersive, multimodal environments measurably improve scientific pattern recognition and analytical confidence.
In a user study with 50 participants analyzing space weather datasets, audio-visual MR conditions produced 70% more identified trends than visual-only analysis.
A parallel system for earthquake disaster response demonstrates how embodied interaction with spatiotemporal data enables faster, more intuitive situational awareness.
A third case study extends these principles to Earth observation, exploring how MR can make NASA's complex geophysical datasets more accessible and actionable for researchers and decision-makers.
Across all three domains, the same design principles emerge: spatial audio, coordinated multiple views, and human-centered interaction drive real analytical gains. Attendees will leave with concrete, research-backed takeaways on what works, what doesn't, and where immersive analytics is headed next.
Session Speaker:
- Disha Sardana, SARP Coding Mentor, NASA
This session was recorded at AWE USA 2026 - the world's leading XR + AI event series. To learn more visit: awexr.com
