Selected Opportunities for Integrating Statistics and Visualization in Multi-dimensional Data Exploration

Johannes Kehrer

MISC, May 27, 2010

Abstract

Visualization and statistics both facilitate the understanding of complex data characteristics, and there is a long history of relations between the two fields. Traditional approaches for data analysis often consider passive visualizations of statistical data properties. Interactive visual analysis, however, as addressed in this talk, allows the iterative exploration and analysis of data in a guided human–computer dialog. Graphical representations of the data and well-proven interaction mechanisms are used to concurrently show, explore, and analyze complex (i.e., time-dependent, multi-variate, and/or multi-dimensional) data. Interesting subsets of the data are interactively selected (brushed) directly on the screen, the relations are investigated in other linked views (including 2D scatterplots, histograms, function graph views, parallel coordinates, but also 3D views of volumetric data). In recent work, we have studied the integration of large amounts of locally aggregated statistical data properties as well as measures of outlyingness in an interactive visual analysis process. The approach is demonstrated on the visual analysis of multi-dimensional climate data. A discussion of possibilities explains how a further combination of interactive statistical plots and proven interaction schemes from visualization research shows great potential for future research.

Published

Talk at EDAVis: Workshop on Exploratory Data Analysis and Visualisation

• Location: Vienna, Austria
• Date: May 27 2010

Media

BibTeX

@misc{kehrer10edaVis,
  author = {Johannes Kehrer},
  title  ={Selected Opportunities for Integrating Statistics and 
Visualization in Multi-dimensional Data Exploration},
  year = {2010},
  month = {May 27},
  howpublished = {Talk at EDAVis: Workshop on Exploratory Data Analysis and Visualisation},
  location = {Vienna, Austria},
  abstract = {Visualization and statistics both facilitate the understanding 
of complex data characteristics, and there is a long history of relations 
between the two fields.  Traditional approaches for data analysis often 
consider passive visualizations of statistical data properties.  
Interactive visual analysis, however, as addressed in this talk, allows 
the iterative exploration and analysis of data in a guided human–computer 
dialog.  Graphical representations of the data and well-proven interaction 
mechanisms are used to concurrently show, explore, and analyze complex (i.e., 
time-dependent, multi-variate, and/or multi-dimensional) data.  Interesting 
subsets of the data are interactively selected (brushed) directly on the 
screen, the relations are investigated in other linked views (including 2D 
scatterplots, histograms, function graph views, parallel coordinates, but 
also 3D views of volumetric data).

In recent work, we have studied the integration of large amounts of locally 
aggregated statistical data properties as well as measures of outlyingness
in an interactive visual analysis process.  The approach is demonstrated on 
the visual analysis of multi-dimensional climate data.  A discussion of 
possibilities explains how a further combination of interactive statistical
plots and proven interaction schemes from visualization research shows great
potential for future research.},


}