Interactive Visual Analysis of Set-Typed Data
Wolfgang Freiler, Kresimir Matkovic, Helwig Hauser
ARTICLE,
IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG),
Oct, 2008
AbstractWhile it is quite typical to deal with attributes of
different data types in the visualization of heterogeneous and multivariate
datasets, most existing techniques still focus on the most usual data types
such as numerical attributes or strings. In this paper we present a new
approach to the interactive visual exploration and analysis of data that
contains attributes which are of set type. A set-typed attribute of a data
item -- like one cell in a table -- has a list of n>=0 elements as its value.
We present the set’o’gram as a new visualization approach to represent data
of set type and to enable interactive visual exploration and analysis. We
also demonstrate how this approach is capable to help in dealing with
datasets that have a larger number of dimensions (more than a dozen or more),
especially also in the context of categorical data. To illustrate the
effectiveness of our approach, we present the interactive visual analysis of
a CRM dataset with data from a questionnaire on the education and shopping
habits of about 90000 people.
Published
IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG)
Media
BibTeX
@article{freiler08setTyped,
author = {Wolfgang Freiler and Kresimir Matkovic and Helwig Hauser},
title = {Interactive Visual Analysis of Set-Typed Data},
year = {2008},
abstract = {While it is quite typical to deal with attributes of
different data types in the visualization of heterogeneous and multivariate
datasets, most existing techniques still focus on the most usual data types
such as numerical attributes or strings. In this paper we present a new
approach to the interactive visual exploration and analysis of data that
contains attributes which are of set type. A set-typed attribute of a data
item -- like one cell in a table -- has a list of n>=0 elements as its value.
We present the set’o’gram as a new visualization approach to represent data
of set type and to enable interactive visual exploration and analysis. We
also demonstrate how this approach is capable to help in dealing with
datasets that have a larger number of dimensions (more than a dozen or more),
especially also in the context of categorical data. To illustrate the
effectiveness of our approach, we present the interactive visual analysis of
a CRM dataset with data from a questionnaire on the education and shopping
habits of about 90000 people.},
month = {Oct},
journal = {IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG)},
event = {IEEE Information Visualization 2008},
location = {Columbus, Ohio, USA},
volume = {14},
number = {6},
pages = {1340--1347},
URL = {http://dx.doi.org/10.1109/TVCG.2008.144},
}
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