CAREER: Towards a Spatial and Embodied End-to-end Data Analysis Workspace in Immersive Environments

This project aims to revolutionize data analysis by harnessing the unique capabilities of immersive technologies, specifically virtual reality (VR) and augmented reality (AR), to design and develop more intuitive and powerful user interfaces. With the increasing complexity and volume of contemporary datasets, there is a pressing need for innovative interfaces that augment analytical capabilities, minimize cognitive load, and facilitate the rapid generation of valuable insights. VR/AR technologies represent the next generation of display and interaction platforms, transcending the limitations of physical screens by enabling users to experience information in two or three dimensions, at any scale, and in any physical location. The gaming and entertainment sectors have experienced considerable success as a result of substantial investments in VR/AR technologies. By integrating immersive technologies into data-intensive workflows, this research aims to reshape the future of workspaces and enhance human analytical capabilities in our increasingly data-driven world. Potential benefits include improved decision-making across sectors like healthcare, finance, and scientific research, while also democratizing data analysis for non-technical users. This could cultivate a more data-literate workforce and society, better equipped to address complex challenges through data-driven approaches. The project's technical approach is structured around three key aims: (1) Designing intuitive 3D data organization interactions that optimize explicit user input while supporting intelligent, implicit system assistance. (2) Developing embodied interactions for data analysis tasks, encompassing visualization authoring and data modeling, with integrated menu systems for precise configurations; and (3) Enabling an end-to-end immersive data analysis pipeline that supports seamless task transitions and enhances data provenance tracking. The research methodology integrates a multi-faceted approach, encompassing controlled laboratory studies, elicitation studies, and longitudinal evaluations, to facilitate the iterative design and validation of the proposed techniques. Through collaborations with domain experts from industry and national laboratories, we will ensure the real-world applicability of our research. This project will produce open-source tools that foster research and education in immersive analytics, thereby enhancing human analytical capabilities through spatial and embodied interactions in immersive environments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.