Sahaf, ZahraMarbouti, MahshidMota, Roberta CabralAlemasoom, HalehMaurer, FrankSousa, Mario CostaMichael Sedlmair and Christian Tominski2017-06-122017-06-122017978-3-03868-042-0https://doi.org/10.2312/eurova.20171116https://diglib.eg.org:443/handle/10.2312/eurova20171116The 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.I.3.3 [Humancentered computing]Visualization/Visualization Application domain/Visual Analytics10.2312/eurova.2017111631-35