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dc.contributor.authorCeneda, Davideen_US
dc.contributor.authorGschwandtner, Theresiaen_US
dc.contributor.authorMay, Thorstenen_US
dc.contributor.authorMiksch, Silviaen_US
dc.contributor.authorStreit, Marcen_US
dc.contributor.authorTominski, Christianen_US
dc.contributor.editorChristian Tominski and Tatiana von Landesbergeren_US
dc.date.accessioned2018-06-02T17:56:58Z
dc.date.available2018-06-02T17:56:58Z
dc.date.issued2018
dc.identifier.isbn978-3-03868-064-2
dc.identifier.urihttp://dx.doi.org/10.2312/eurova.20181107
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurova20181107
dc.description.abstractGuidance methods have the potential of bringing considerable benefits to Visual Analytics (VA), alleviating the burden on the user and allowing a positive analysis outcome. However, the boundary between conventional VA approaches and guidance is not sharply defined. As a consequence, framing existing guidance methods is complicated and the development of new approaches is also compromised. In this paper, we try to bring these concepts in order, defining clearer boundaries between guidance and no-guidance. We summarize our findings in form of a decision tree that allows scientists and designers to easily frame their solutions. Finally, we demonstrate the usefulness of our findings by applying our guideline to a set of published approaches.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectVisual analytics
dc.subjectVisualization theory
dc.subjectconcepts and paradigms
dc.subjectInformation systems
dc.subjectDecision support systems
dc.titleGuidance or No Guidance? A Decision Tree Can Helpen_US
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)
dc.description.sectionheadersAnalytics and Guidance
dc.identifier.doi10.2312/eurova.20181107
dc.identifier.pages19-23


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