An application of multivariate statistical analysis for Query-Driven Visualization

© 2011 IEEE

Détails bibliographiques
Publié dans:IEEE transactions on visualization and computer graphics. - 1996. - 17(2011), 3 vom: 25. März, Seite 264-75
Auteur principal: Gosink, Luke J (Auteur)
Autres auteurs: Garth, Christoph, Anderson, John C, Bethel, E Wes, Joy, Kenneth I
Format: Article en ligne
Langue:English
Publié: 2011
Accès à la collection:IEEE transactions on visualization and computer graphics
Sujets:Journal Article Research Support, U.S. Gov't, Non-P.H.S.
Description
Résumé:© 2011 IEEE
Driven by the ability to generate ever-larger, increasingly complex data, there is an urgent need in the scientific community for scalable analysis methods that can rapidly identify salient trends in scientific data. Query-Driven Visualization (QDV) strategies are among the small subset of techniques that can address both large and highly complex data sets. This paper extends the utility of QDV strategies with a statistics-based framework that integrates nonparametric distribution estimation techniques with a new segmentation strategy to visually identify statistically significant trends and features within the solution space of a query. In this framework, query distribution estimates help users to interactively explore their query's solution and visually identify the regions where the combined behavior of constrained variables is most important, statistically, to their inquiry. Our new segmentation strategy extends the distribution estimation analysis by visually conveying the individual importance of each variable to these regions of high statistical significance. We demonstrate the analysis benefits these two strategies provide and show how they maybe used to facilitate the refinement of constraints over variables expressed in a user's query. We apply our method to data sets from two different scientific domains to demonstrate its broad applicability
Description:Date Completed 20.04.2012
Date Revised 24.04.2012
published: Print
Citation Status MEDLINE
ISSN:1941-0506
DOI:10.1109/TVCG.2010.80