Show simple item record

dc.contributor.authorButcher, Peter*
dc.contributor.authorJohn, Nigel W.*
dc.contributor.authorRitsos, Panagiotis D.*
dc.date.accessioned2019-02-20T14:17:30Z
dc.date.available2019-02-20T14:17:30Z
dc.date.issued2019-05
dc.identifier.citationButcher, P.W.S., John, N.W., & Ritsos, P.D. (2019). VRIA - A Framework for Immersive Analytics on the Web. In Proceedings of ACM CHI Conference on Human Factors in Computing Systems, Glasgow, UKen
dc.identifier.isbn9781450359719
dc.identifier.doi10.1145/3290607.3312798
dc.identifier.urihttp://hdl.handle.net/10034/621901
dc.description.abstractWe report on the design, implementation and evaluation of <VRIA>, a framework for building immersive analytics (IA) solutions inWeb-based Virtual Reality (VR), built upon WebVR, A-Frame, React and D3. The recent emergence of affordable VR interfaces have reignited the interest of researchers and developers in exploring new, immersive ways to visualize data. In particular, the use of open-standards web-based technologies for implementing VR in a browser facilitates the ubiquitous and platform-independent adoption of IA systems. Moreover, such technologies work in synergy with established visualization libraries, through the HTML document object model (DOM). We discuss high-level features of <VRIA> and present a preliminary user experience evaluation of one of our use-cases.
dc.language.isoenen
dc.publisherACMen
dc.relation.urlhttps://ieeexplore.ieee.org/document/8440821/en
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.titleVRIA - A Framework for Immersive Analytics on the Weben
dc.typeMeetings and Proceedingsen
dc.contributor.departmentUniversity of Chester and Bangor Universityen
dc.identifier.journalProceedings of ACM CHI Conference on Human Factors in Computing Systems 2019
dc.date.accepted2019-02-08
or.grant.openaccessYesen
rioxxterms.funderunfundeden_US
rioxxterms.identifier.projectunfundeden_US
rioxxterms.versionAMen
rioxxterms.licenseref.startdate2019-05-01


Files in this item

Thumbnail
Name:
ACM_CHI2019_LBW.pdf
Size:
3.062Mb
Format:
PDF
Request:
Main Article

This item appears in the following Collection(s)

Show simple item record

https://creativecommons.org/licenses/by-nc-nd/4.0/
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/