VRIA: A Web-based Framework for Creating Immersive Analytics Experiences

Research output: Contribution to journalArticlepeer-review

Standard Standard

VRIA: A Web-based Framework for Creating Immersive Analytics Experiences. / Butcher, Peter; John, Nigel W.; Ritsos, Panagiotis D.
In: IEEE Transactions on visualization and computer graphics, Vol. 27, No. 7, 01.07.2021, p. 3213 - 3225.

Research output: Contribution to journalArticlepeer-review

HarvardHarvard

Butcher, P, John, NW & Ritsos, PD 2021, 'VRIA: A Web-based Framework for Creating Immersive Analytics Experiences', IEEE Transactions on visualization and computer graphics, vol. 27, no. 7, pp. 3213 - 3225. https://doi.org/10.1109/TVCG.2020.2965109

APA

Butcher, P., John, N. W., & Ritsos, P. D. (2021). VRIA: A Web-based Framework for Creating Immersive Analytics Experiences. IEEE Transactions on visualization and computer graphics, 27(7), 3213 - 3225. https://doi.org/10.1109/TVCG.2020.2965109

CBE

Butcher P, John NW, Ritsos PD. 2021. VRIA: A Web-based Framework for Creating Immersive Analytics Experiences. IEEE Transactions on visualization and computer graphics. 27(7):3213 - 3225. https://doi.org/10.1109/TVCG.2020.2965109

MLA

Butcher, Peter, Nigel W. John, and Panagiotis D. Ritsos. "VRIA: A Web-based Framework for Creating Immersive Analytics Experiences". IEEE Transactions on visualization and computer graphics. 2021, 27(7). 3213 - 3225. https://doi.org/10.1109/TVCG.2020.2965109

VancouverVancouver

Butcher P, John NW, Ritsos PD. VRIA: A Web-based Framework for Creating Immersive Analytics Experiences. IEEE Transactions on visualization and computer graphics. 2021 Jul 1;27(7):3213 - 3225. Epub 2020 Jan 9. doi: 10.1109/TVCG.2020.2965109

Author

Butcher, Peter ; John, Nigel W. ; Ritsos, Panagiotis D. / VRIA: A Web-based Framework for Creating Immersive Analytics Experiences. In: IEEE Transactions on visualization and computer graphics. 2021 ; Vol. 27, No. 7. pp. 3213 - 3225.

RIS

TY - JOUR

T1 - VRIA: A Web-based Framework for Creating Immersive Analytics Experiences

AU - Butcher, Peter

AU - John, Nigel W.

AU - Ritsos, Panagiotis D.

PY - 2021/7/1

Y1 - 2021/7/1

N2 - We present , a Web-based framework for creating Immersive Analytics (IA) experiences in Virtual Reality. 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 ubiquitous and platform-independent. Moreover, by using WebVR’s progressive enhancement, the experiences creates are accessible on a plethora of devices. We elaborate on our motivation for focusing on open-standards Web technologies, present the 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 . Finally, we discuss current limitations of our framework, the lessons learned from its development, and outline further extensions.

AB - We present , a Web-based framework for creating Immersive Analytics (IA) experiences in Virtual Reality. 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 ubiquitous and platform-independent. Moreover, by using WebVR’s progressive enhancement, the experiences creates are accessible on a plethora of devices. We elaborate on our motivation for focusing on open-standards Web technologies, present the 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 . Finally, we discuss current limitations of our framework, the lessons learned from its development, and outline further extensions.

U2 - 10.1109/TVCG.2020.2965109

DO - 10.1109/TVCG.2020.2965109

M3 - Article

VL - 27

SP - 3213

EP - 3225

JO - IEEE Transactions on visualization and computer graphics

JF - IEEE Transactions on visualization and computer graphics

SN - 1077-2626

IS - 7

ER -