Grants and Contributions:

Grant or Award spanning more than one fiscal year (2017-2018 to 2019-2020).

Immersive analytics combines data science, scientific visualization techniques, 3D interfaces, and mixed reality environments to support improved analytical reasoning and decision making when exploring complex datasets. Some examples of customized, high-end, blended reality environments include: CAVE2 at UIC, YURT at Brown, Reality Deck at SUNY, Augmentarium at University of Maryland, HIVE at Duke, the five-sided La Cueva Grande at LANL, AlloSphere at UCSB, GigaPixel Display Laboratory and Visionarium at Virginia Tech.x000D
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In this project we will explore representative complex datasets with newly emerging, commodity-priced technologies such as Mixed Reality (MR), 3D input devices, and Natural Language Processing (NLP). Customer behaviour patterns, product analysis telemetry, and resource utilization in a data center are common themes in Canadian industry that could benefit from these results. Specifically, we plan to address open questions in an industry relevant problem at the intersection of systems, analytics, and information visualization by considering deployment strategies for containers in a data center. The three key questions this research will address are:x000D
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1) What interaction mechanisms are most effective at promoting engagement?x000D
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2) What are the most seamless ways of elucidating thex000D
inter-relationship of disparate data sets?x000D
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3) What are the best models for group interactions in a virtual environment?x000D
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