Supporting Co-Located Collaboration in Large-Scale Hybrid Immersive Environments

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These are videos from my talk for the 2016 Media Arts & Technology Seminar Series @ UCSB. While at UCSB, I had the chance to walk in the Allosphere: it's by far the most immersive large scale system I've ever seen!


 Abstract: In the domain of large-scale visualization instruments, Hybrid Reality Environments (HREs) are a recent innovation that combines the best-in-class capabilities of immersive environments, with the best-in-class capabilities of ultra-high-resolution display walls. Co-located research groups in HREs tend to work on a variety of tasks during a research session (sometimes in parallel), and these tasks require 2D data views, 3D views, linking between them and the ability to bring in (or hide) data quickly as needed. Addressing these needs requires a matching software infrastructure that fully leverages the technological affordances offered by these new instruments. I detail the requirements of such infrastructure and outline the model of an operating system for Hybrid Reality Environments: I present an implementation of core components of this model, called Omegalib. Omegalib is designed to support dynamic reconfigurability of the display environment: areas of the display can be interactively allocated to 2D or 3D workspaces as needed.
 
Alessandro Febretti - full talk - part 1/2 from mat.ucsb on Vimeo.
Alessandro Febretti - full talk - part 2/2 from mat.ucsb on Vimeo.

Comments

dean said…
This article gives a useful perspective on how large-scale Hybrid Reality Environments can support several researchers working together in the same physical space. The requirement to switch between 2D data views, 3D environments, linked views, and quickly changing datasets shows why a conventional display setup is not always sufficient for collaborative research. The idea of dynamically allocating parts of the display to different workspaces is particularly interesting.

The emphasis on combining immersive environments with ultra-high-resolution display walls makes Data Visualization Training especially relevant, since the challenge goes beyond simply rendering graphics and involves organizing multiple visual representations so researchers can interact with complex information effectively. Omegalib's support for dynamically reconfiguring these visualization spaces is a practical example of this approach.
September 10, 2026 at 10:16 AM
dean said…
The infrastructure requirements described here also demonstrate why scalable systems are important when multiple users and large collections of visual data must be handled simultaneously. This connects with Big Data Projects, particularly from the perspective of building computing and visualization environments capable of supporting complex data-intensive research workflows rather than treating visualization as an isolated display task.
September 10, 2026 at 10:16 AM
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