Resolving Conflicting Insights in Asynchronous Collaborative Visual Analysis

dc.contributor.authorLi, Jianping Kelvinen_US
dc.contributor.authorXu, Shenyuen_US
dc.contributor.authorYe, Yecong (Chris)en_US
dc.contributor.authorMa, Kwan-Liuen_US
dc.contributor.editorViola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatianaen_US
dc.date.accessioned2020-05-24T13:01:41Z
dc.date.available2020-05-24T13:01:41Z
dc.date.issued2020
dc.description.abstractAnalyzing large and complex datasets for critical decision making can benefit from a collective effort involving a team of analysts. However, insights and findings from different analysts are often incomplete, disconnected, or even conflicting. Most existing analysis tools lack proper support for examining and resolving the conflicts among the findings in order to consolidate the results of collaborative data analysis. In this paper, we present CoVA, a visual analytics system incorporating conflict detection and resolution for supporting asynchronous collaborative data analysis. By using a declarative visualization language and graph representation for managing insights and insight provenance, CoVA effectively leverages distributed revision control workflow from software engineering to automatically detect and properly resolve conflicts in collaborative analysis results. In addition, CoVA provides an effective visual interface for resolving conflicts as well as combining the analysis results. We conduct a user study to evaluate CoVA for collaborative data analysis. The results show that CoVA allows better understanding and use of the findings from different analysts.en_US
dc.description.number3
dc.description.sectionheadersVisual Analytics for Problem Solving
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume39
dc.identifier.doi10.1111/cgf.13997
dc.identifier.issn1467-8659
dc.identifier.pages497-509
dc.identifier.urihttps://doi.org/10.1111/cgf.13997
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13997
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/]
dc.titleResolving Conflicting Insights in Asynchronous Collaborative Visual Analysisen_US
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