ReLive : Bridging In-Situ and Ex-Situ Visual Analytics for Analyzing Mixed Reality User Studies

dc.contributor.authorHubenschmid, Sebastian
dc.contributor.authorWieland, Jonathan
dc.contributor.authorFink, Daniel Immanuel
dc.contributor.authorBatch, Andrea
dc.contributor.authorZagermann, Johannes
dc.contributor.authorElmqvist, Niklas
dc.contributor.authorReiterer, Harald
dc.date.accessioned2022-03-10T12:15:56Z
dc.date.available2022-03-10T12:15:56Z
dc.date.issued2022eng
dc.description.abstractThe nascent field of mixed reality is seeing an ever-increasing need for user studies and field evaluation, which are particularly challenging given device heterogeneity, diversity of use, and mobile deployment. Immersive analytics tools have recently emerged to support such analysis in situ, yet the complexity of the data also warrants an ex-situ analysis using more traditional non-immersive visual analytics setups. To bridge the gap between both approaches, we introduce ReLive: a mixed-immersion visual analytics framework for exploring and analyzing mixed reality user studies. ReLive combines an in-situ virtual reality view with a complementary ex-situ desktop view. While the virtual reality view allows users to relive interactive spatial recordings replicating the original study, the synchronized desktop view provides a familiar interface for analyzing aggregated data. We validated our concepts in a two-step evaluation consisting of a design walkthrough and an empirical expert user study.eng
dc.description.versionacceptedeng
dc.identifier.doi10.1145/3491102.3517550eng
dc.identifier.ppn1795283467
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/56817
dc.language.isoengeng
dc.rightsterms-of-use
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/
dc.subjectImmersive analytics; visual analytics; data visualization; virtual realityeng
dc.subject.ccsHuman-centered computing > Visualization > Visualization application domains > Visual analytics; 500
dc.subject.ccsHuman-centered computing > Human computer interaction (HCI) > Interaction paradigms > Virtual reality; 500
dc.subject.ccsHuman-centered computing > Human computer interaction (HCI) > HCI design and evaluation methods > User studies; 100
dc.subject.ddc004eng
dc.titleReLive : Bridging In-Situ and Ex-Situ Visual Analytics for Analyzing Mixed Reality User Studieseng
dc.typeINPROCEEDINGSeng
dspace.entity.typePublication
kops.conferencefieldCHI Conference on Human Factors in Computing Systems (CHI '22), 29. Apr. 2022 - 5. Mai 2022, New Orleans, LA, USA
kops.date.conferenceEnd2022-05-05eng
kops.date.conferenceStart2022-04-29eng
kops.flag.knbibliographytrue
kops.identifier.nbnurn:nbn:de:bsz:352-2-1hq3z7al137j00
kops.location.conferenceNew Orleans, LA, USAeng
kops.relation.lsfProjectTitleSFB TRR 161 TP C 01 Quantitative Messung von Interaktioneng
kops.relation.lsfProjectTitleSMARTACT Teilprojekt 6: Smartmobility / SMARTACT 2 Teilprojekt 6eng
kops.sourcefield<i>CHI Conference on Human Factors in Computing Systems (CHI ’22)</i>. New York, NY: ACM, 2022. ISBN 978-1-4503-9157-3. Available under: doi: 10.1145/3491102.3517550
kops.title.conferenceCHI Conference on Human Factors in Computing Systems (CHI '22)eng
source.identifier.isbn978-1-4503-9157-3eng
source.publisherACMeng
source.publisher.locationNew York, NYeng
source.titleCHI Conference on Human Factors in Computing Systems (CHI ’22)eng
temp.submission.doihttps://doi.org/10.1145/3491102.3517550
temp.submission.source<i>CHI Conference on Human Factors in Computing Systems (CHI ’22)</i>. New York, NY: ACM, 2022. ISBN 978-1-4503-9157-3. Available under: doi: 10.1145/3491102.3517550
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