Panagiotis D. Ritsos

MEng PhD Essex, FHEA

Lecturer in Visualization

Immersive Environments Lab
Visualization, Data, Modelling and
Graphics (VDMG) research group,

School of Computer Science
and Electronic Engineering,

Bangor University,
Dean Street, Bangor,
Gwynedd, UK, LL57 1UT

IEEE TVCG journal paper & a poster to be presented in IEEE VIS 2020

WebVR-based visualizations built with VRIA

Our IEEE TVCG journal article “VRIA: A Web-based Framework for Creating Immersive Analytics Experiences” will be presented at the virtual IEEE VIS 2020 IEEE VIS 2020.

<VRIA> is a Web-based framework, built for creating Immersive Analytics (IA) experiences in Virtual Reality. <VRIA> is built upon WebVR, A-Frame, React and D3.js, and offers a visualization creation workflow which enables users, of different levels of expertise, to rapidly develop Immersive Analytics experiences for the Web. More info on this paper can be found here, whereas the <VRIA> framework can be found on GitHub.

WebVR-based Hapiness Data from Hedonometer.org

We will also be presenting a poster, titled “Immersive visualisation of COVID-19 UK travel and US happiness data”, written with our undergraduate interns, Rhys Williams and Dan Farmer, along with Prof J.C. Roberts. The work was supported by the Bangor University Undergraduate Internship Scheme.

Reference

P. W. S. Butcher, N. W. John, and P. D. Ritsos, “VRIA: A Web-based Framework for Creating Immersive Analytics Experiences,” IEEE Transactions on Visualization and Computer Graphics (Early Access)), Jan. 2020. We present <VRIA>, a Web-based framework for creating Immersive Analytics (IA) experiences in Virtual Reality. <VRIA> is built upon WebVR, A-Frame, React and D3.js, and offers a visualization creation workflow which enables users, of different levels of expertise, to rapidly develop Immersive Analytics experiences for the Web. The use of these open-standards Web-based technologies allows us to implement VR experiences in a browser and offers strong synergies with popular visualization libraries, through the HTML Document Object Model (DOM). This makes <VRIA> ubiquitous and platform-independent. Moreover, by using WebVR’s progressive enhancement, the experiences <VRIA> creates are accessible on a plethora of devices. We elaborate on our motivation for focusing on open-standards Web technologies, present the <VRIA> creation workflow and detail the underlying mechanics of our framework. We also report on techniques and optimizations necessary for implementing Immersive Analytics experiences on the Web, discuss scalability implications of our framework, and present a series of use case applications to demonstrate the various features of <VRIA>. Finally, we discuss current limitations of our framework, the lessons learned from its development, and outline further extensions.
[Abstract]   [PDF]   [BibTex]   [doi:10.1109/TVCG.2020.2965109]   [Code]  

R. L. Williams, D. Farmer, J. C. Roberts, and P. D. Ritsos, “Immersive visualisation of COVID-19 UK travel and US happiness data,” in Posters presented at the IEEE Conference on Visualization (IEEE VIS 2020), Virtual Event, 2020. The global COVID-19 pandemic has had great affect on the lives of everyone, from changing how children are educated to how or whether at all, we travel, go to work or do our shopping. Consequently, not only has people’s happiness changed throughout the pandemic, but there has been less vehicles on the roads. We present work to visualise both US happiness and UK travel data, as examples, in immersive environments. These impromptu visualisations encourage discussion and engagement with these topics, and can help people see the data in an alternative way.
[Abstract]   [PDF]   [BibTex]   [URL]