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DataMeadow: A Visual Canvas for Analysis of Large-Scale Multivariate Data

Niklas Elmqvist ; John Stasko ; Philippas Tsigas (Institutionen för data- och informationsteknik, Datavetenskap, Datakommunikation och distribuerade system (Chalmers))
Göteborg : Chalmers University of Technology, 2007. - 18 s.

Supporting visual analytics of multiple large-scale multidimensional datasets requires a high degree of interactivity and user control beyond the conventional challenges of visualizing such datasets. We present the DataMeadow, a visual canvas providing rich interaction for constructing visual queries using graphical set representations called DataRoses. A DataRose is essentially a starplot of selected columns in a dataset displayed as multivariate visualizations with dynamic query sliders integrated into each axis. The purpose of the DataMeadow is to allow users to create advanced visual queries by iteratively selecting and filtering into the multidimensional data. Furthermore, the canvas provides a clear history of the analysis that can be annotated to facilitate dissemination of analytical results to outsiders. Towards this end, the DataMeadow has a direct manipulation interface for selection, filtering, and creation of sets, subsets, and data dependencies using both simple and complex mouse gestures. We have evaluated our system using a qualitative expert review involving two researchers working in the area. Results from this review are favorable for our new method.

Nyckelord: Visual Analytics, Information Visualization, multidimensional datasets

Denna post skapades 2007-04-20. Senast ändrad 2013-08-02.
CPL Pubid: 40753


Institutioner (Chalmers)

Institutionen för data- och informationsteknik, Datavetenskap, Datakommunikation och distribuerade system (Chalmers) (2005-2007)



Chalmers infrastruktur

Ingår i serie

Technical report - Department of Computer Science and Engineering, Chalmers University of Technology and Göteborg University