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dc.contributor.authorSahaf, Zahraen_US
dc.contributor.authorMarbouti, Mahshiden_US
dc.contributor.authorMota, Roberta Cabralen_US
dc.contributor.authorAlemasoom, Halehen_US
dc.contributor.authorMaurer, Franken_US
dc.contributor.authorSousa, Mario Costaen_US
dc.contributor.editorMichael Sedlmair and Christian Tominskien_US
dc.date.accessioned2017-06-12T05:16:25Z
dc.date.available2017-06-12T05:16:25Z
dc.date.issued2017
dc.identifier.isbn978-3-03868-042-0
dc.identifier.urihttp://dx.doi.org/10.2312/eurova.20171116
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurova20171116
dc.description.abstractThe fatal hazards associated with pipeline incidents as well as their frequent occurrence motivate pipeline analysts to learn from historical events and to use that information to prevent future ones by taking proper action. However, the incredible wealth of information contained in pipeline incidents data sets makes it considerably challenging to explore such data. Our solution comprises a visual exploration prototype that aims to help pipeline analysts overcome these difficulties. In this sense, it applies different visual analytical and exploration techniques over the raw pipeline incident data to uncover hidden patterns, unknown correlations, tendencies, and other meaningful information. In that regard, we implemented a prototype which consists of four different views that user can with: a map view that provides spatial information, a chart view that highlights tendencies, a Parallel Coordinates view that discloses hidden patterns and a decision tree view that extracts crucial rules and relations in data.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.3 [Human
dc.subjectcentered computing]
dc.subjectVisualization/Visualization Application domain/Visual Analytics
dc.titlePipeVis: Interactive Visual Exploration of Pipeline Incident Dataen_US
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)
dc.description.sectionheadersApplications
dc.identifier.doi10.2312/eurova.20171116
dc.identifier.pages31-35


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