Towards Quantitative Visual Analytics with Structured Brushing and Linked Statistics

Simple item page
dc.contributor.authorRadoš, Sanjinen_US
dc.contributor.authorSplechtna, Raineren_US
dc.contributor.authorMatkovic, Kresimiren_US
dc.contributor.authorDuras, Marioen_US
dc.contributor.authorGröller, Eduarden_US
dc.contributor.authorHauser, Helwigen_US
dc.contributor.editorKwan-Liu Ma and Giuseppe Santucci and Jarke van Wijken_US
dc.date.accessioned2016-06-09T09:32:48Z
dc.date.available2016-06-09T09:32:48Z
dc.date.issued2016en_US
dc.description.abstractUntil now a lot of visual analytics predominantly delivers qualitative results-based, for example, on a continuous color map or a detailed spatial encoding. Important target applications, however, such as medical diagnosis and decision making, clearly benefit from quantitative analysis results. In this paper we propose several specific extensions to the well-established concept of linking&brushing in order to make the analysis results more quantitative. We structure the brushing space in order to improve the reproducibility of the brushing operation, e.g., by introducing the percentile grid. We also enhance the linked visualization with overlaid descriptive statistics to enable a more quantitative reading of the resulting focus+context visualization. Additionally, we introduce two novel brushing techniques: the percentile brush and the Mahalanobis brush. Both use the underlying data to support statistically meaningful interactions with the data. We illustrate the use of the new techniques in the context of two case studies, one based on meteorological data and the other one focused on data from the automotive industry where we evaluate a shaft design in the context of mechanical power transmission in cars.en_US
dc.description.number3en_US
dc.description.sectionheadersCoordinated Views and Interaction Designen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume35en_US
dc.identifier.doi10.1111/cgf.12901en_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages251-260en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12901en_US
dc.identifier.urihttps://diglib.eg.org:443/handle/10
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.6 [Computer Graphics]en_US
dc.subjectMethodology and Techniquesen_US
dc.subjectInteraction techniquesen_US
dc.titleTowards Quantitative Visual Analytics with Structured Brushing and Linked Statisticsen_US
Files
Collections
35-Issue 3
EuroVis16: Eurographics Conference on Visualization