Panagiotis D. Ritsos

MEng PhD Essex, FHEA

Senior Lecturer in Visualization

XReality, Visualization and
Analytics (XRVA) Lab
Visualization, Data, Modelling and
Graphics (VDMG) research group,
School of Computer Science
and Engineering,
Bangor University,
Dean Street, Bangor,
Gwynedd, UK, LL57 1UT

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  p.ritsos (at) bangor.ac.uk
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Journal paper in IEEE TVCG

January 2020 IEEE, journal, VR, XR, InfoVis, WebXR, immersive analytics

WebVR-based visualizations built with VRIA

Our journal article “VRIA: A Web-based Framework for Creating Immersive Analytics Experiences” has been published in IEEE Transactions of Visualization and Computer Graphics (TVCG).

<VRIA> is a framework for building Immersive Analytics solutions in VR, using standards-based Web-technologies. It is built using WebVR, A-Frame and React and the resulting VR solutions can be experienced through a WebVR-compliant browser on a variety of devices, ranging from smartphones to HMD-equipped desktop computers. <VRIA> uses a declarative format for specifying visualization types through simple configuration files, simplifying visualization prototyping, data binding and interaction configuration.

<VRIA>’s visualization creation workflow (below, Figure 1.) provides different development paths for novice, intermediate and expert developers, and makes (optional) use of a dedicated visualization builder (show at the top), a Web-based interface that enables developers to easily prototype IA experiences and export their visualization configurations. These configurations can be further customized via the <VRIA> API to create new immersive depictions. Our paper presents a series of use cases that demonstrate the functionality and versatility of <VRIA>, including early extensions to MR space.

Visualization creation workflow demonstrating how <VRIA> is suitable for users with different levels of programming experience. Novice users can upload datasets to the <VRIA> builder tool and quickly produce immersive visualizations without coding. Intermediate users can use the builder to create a visualization config file or write one from scratch to use in their application. Finally, advanced users can make use of <VRIA> ’s API to develop additional features.
Figure 1: Visualization creation workflow demonstrating how <VRIA> is suitable for users with different levels of programming experience. Novice users can upload datasets to the <VRIA> builder tool and quickly produce immersive visualizations without coding. Intermediate users can use the builder to create a visualization config file or write one from scratch to use in their application. Finally, advanced users can make use of <VRIA> ’s API to develop additional features. [PNG]

More information on the VRIA framework can be found here.

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, vol. 27, no. 07, pp. 3213–3225, Jul. 2021. 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]   [Details]   [PDF]   [doi:10.1109/TVCG.2020.2965109]   [Presented at IEEE VIS 2020]