Steering the Craft: UI Elements and Visualizations for Supporting Progressive Visual Analytics

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dc.contributor.authorBadam, Sriram Karthiken_US
dc.contributor.authorElmqvist, Niklasen_US
dc.contributor.authorFekete, Jean-Danielen_US
dc.contributor.editorHeer, Jeffrey and Ropinski, Timo and van Wijk, Jarkeen_US
dc.date.accessioned2017-06-12T05:23:06Z
dc.date.available2017-06-12T05:23:06Z
dc.date.issued2017
dc.description.abstractProgressive visual analytics (PVA) has emerged in recent years to manage the latency of data analysis systems. When analysis is performed progressively, rough estimates of the results are generated quickly and are then improved over time. Analysts can therefore monitor the progression of the results, steer the analysis algorithms, and make early decisions if the estimates provide a convincing picture. In this article, we describe interface design guidelines for helping users understand progressively updating results and make early decisions based on progressive estimates. To illustrate our ideas, we present a prototype PVA tool called INSIGHTSFEED for exploring Twitter data at scale. As validation, we investigate the tradeoffs of our tool when exploring a Twitter dataset in a user study. We report the usage patterns in making early decisions using the user interface, guiding computational methods, and exploring different subsets of the dataset, compared to sequential analysis without progression.en_US
dc.description.number3
dc.description.sectionheadersInteraction and Presentation
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume36
dc.identifier.doi10.1111/cgf.13205
dc.identifier.issn1467-8659
dc.identifier.pages491-502
dc.identifier.urihttps://doi.org/10.1111/cgf.13205
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13205
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectProgressive visual analytics (PVA) has emerged in recent years to manage the latency of data analysis systems. When analysis is performed progressively
dc.subjectrough estimates of the results are generated quickly and are then improved over time. Analysts can therefore monitor the progression of the results
dc.subjectsteer the analysis algorithms
dc.subjectand make early decisions if the estimates provide a convincing picture. In this article
dc.subjectwe describe interface design guidelines for helping users understand progressively updating results and make early decisions based on progressive estimates. To illustrate our ideas
dc.subjectwe present a prototype PVA tool called INSIGHTSFEED for exploring Twitter data at scale. As validation
dc.subjectwe investigate the tradeoffs of our tool when exploring a Twitter dataset in a user study. We report the usage patterns in making early decisions using the user interface
dc.subjectguiding computational methods
dc.subjectand exploring different subsets of the dataset
dc.subjectcompared to sequential analysis without progression.
dc.titleSteering the Craft: UI Elements and Visualizations for Supporting Progressive Visual Analyticsen_US
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