Brushing Dimensions – A Dual Visual Analysis Model for High-dimensional Data
Abstract
In many application fields, data analysts have to deal with datasets that contain many expressions per item. The effective analysisof such multivariate datasets is dependent on the users ability to understand both the intrinsic dimensionality of the dataset as well as the distribution of the dependent values with respect to the dimensions. In this paper, we propose a visualization model that enables the joint interactive visual analysis of multivariate datasets with respect to their dimensions as well as with respect to the actual data values. We describe a dual setting of visualization and interaction in items space and in dimensions space. The visualization of items is linked to the visualization of dimensions with brushing and focus+context visualization. With this approach, the user is able to jointly study the structure of the dimensions space as well as the distribution of data items with respect to the dimensions. Even though the proposed visualization model is general, we demonstrate its application in the context of a DNA microarray data analysis.
C. Turkay, P. Filzmoser, and H. Hauser, "Brushing Dimensions – A Dual Visual Analysis Model for High-dimensional Data," IEEE Transactions on Visualization and Computer Graphics, vol. 17, iss. 12, p. 2591–2599, 2011.
[BibTeX]
In many application fields, data analysts have to deal with datasets that contain many expressions per item. The effective analysisof such multivariate datasets is dependent on the users ability to understand both the intrinsic dimensionality of the dataset as well as the distribution of the dependent values with respect to the dimensions. In this paper, we propose a visualization model that enables the joint interactive visual analysis of multivariate datasets with respect to their dimensions as well as with respect to the actual data values. We describe a dual setting of visualization and interaction in items space and in dimensions space. The visualization of items is linked to the visualization of dimensions with brushing and focus+context visualization. With this approach, the user is able to jointly study the structure of the dimensions space as well as the distribution of data items with respect to the dimensions. Even though the proposed visualization model is general, we demonstrate its application in the context of a DNA microarray data analysis.
@ARTICLE {turkay11brushingDimensions,
author = "Cagatay Turkay and Peter Filzmoser and Helwig Hauser",
title = "Brushing Dimensions -- A Dual Visual Analysis Model for High-dimensional Data",
journal = "IEEE Transactions on Visualization and Computer Graphics",
year = "2011",
volume = "17",
number = "12",
pages = "2591--2599",
abstract = "In many application fields, data analysts have to deal with datasets that contain many expressions per item. The effective analysisof such multivariate datasets is dependent on the users ability to understand both the intrinsic dimensionality of the dataset as well as the distribution of the dependent values with respect to the dimensions. In this paper, we propose a visualization model that enables the joint interactive visual analysis of multivariate datasets with respect to their dimensions as well as with respect to the actual data values. We describe a dual setting of visualization and interaction in items space and in dimensions space. The visualization of items is linked to the visualization of dimensions with brushing and focus+context visualization. With this approach, the user is able to jointly study the structure of the dimensions space as well as the distribution of data items with respect to the dimensions. Even though the proposed visualization model is general, we demonstrate its application in the context of a DNA microarray data analysis.",
images = "images/turkay11dimensions.png, images/turkay11dimensions3.png, images/turkay11dimensions2.png",
thumbnails = "images/turkay11dimensions_thumb.png, images/turkay11dimensions3_thumb.png, images/turkay11dimensions2_thumb.png",
event = "IEEE Information Visualization Conference 2011",
location = "Providence, RI, USA",
url = "//dx.doi.org/10.1109/TVCG.2011.178"
}