Wolfgang Freiler
Set Type Enabled Information Visualization
[image] [
paper]
Information
- Publication Type: Master Thesis
- Workgroup(s)/Project(s):
- Date: March 2008
- Diploma Examination: 11. March 2008
- First Supervisor:
Abstract
Information Visualization is a research area in the eld of computer graphics that deals with visual representations of abstract and usually multidimensional data. This data can origin from questionnaires, elections, measurements or simulations. Apart from specialized tools, that are made for a special purpose, there are general purpose tools, that can be used to analyze many kinds of di erent data. These tools are made to handle di erent data types, like numeric or categorical values, some also support more advanced data types, like time series data or hierarchical data. In this document, the data type set will be introduced into the general purpose visualization tool ComVis. A set is a collection of multiple elements, that can also be empty. In many cases, a dimension with the data type set can replace multiple categorical dimensions and make data analysis and exploration more ecient and complex datasets easier to understand. This work will not only explain, how to use sets to explore datasets, but also introduce a new specialized view based on a histogram view, that is dedicated to the use of sets. Of course, most of the already existing views have been modi ed to use sets, otherwise the newly added data type would be dicult to use either. Especially views that can display multiple dimensions were a challenge, because they allow the user to mix sets with other data types. Apart from the use of sets in various views, some additional topics are covered in this document. The conversion of existing categorical data is a very important feature, as well as a fast and ecient data structure. The existing methods for user interaction like brushing and linked coordinated views have to work as expected for all supported data types. A set should not be seen as a new arti cial data type, that we have to convert existing data to, but as the natural data type in many applications. Instead of introducing another conversion step for our data, we can avoid converting data with multiple related attributes to a range of categorical dimensions. Using sets is also an ecient way of dimension reduction, and can reduce the complexity of a dataset, as well as the amount of views needed for exploration. Additionally, there are some examples on how to take advantage of sets when analyzing a real-world dataset. Some special features of this dataset as well as some erroneous entries are easier to nd by using sets and views that support them.Additional Files and Images
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No further information available.BibTeX
@mastersthesis{freiler-2008-ste,
title = "Set Type Enabled Information Visualization",
author = "Wolfgang Freiler",
year = "2008",
abstract = "Information Visualization is a research area in the eld of
computer graphics that deals with visual representations of
abstract and usually multidimensional data. This data can
origin from questionnaires, elections, measurements or
simulations. Apart from specialized tools, that are made for
a special purpose, there are general purpose tools, that can
be used to analyze many kinds of di erent data. These tools
are made to handle di erent data types, like numeric or
categorical values, some also support more advanced data
types, like time series data or hierarchical data. In this
document, the data type set will be introduced into the
general purpose visualization tool ComVis. A set is a
collection of multiple elements, that can also be empty. In
many cases, a dimension with the data type set can replace
multiple categorical dimensions and make data analysis and
exploration more ecient and complex datasets easier to
understand. This work will not only explain, how to use sets
to explore datasets, but also introduce a new specialized
view based on a histogram view, that is dedicated to the use
of sets. Of course, most of the already existing views have
been modi ed to use sets, otherwise the newly added data
type would be dicult to use either. Especially views that
can display multiple dimensions were a challenge, because
they allow the user to mix sets with other data types. Apart
from the use of sets in various views, some additional
topics are covered in this document. The conversion of
existing categorical data is a very important feature, as
well as a fast and ecient data structure. The existing
methods for user interaction like brushing and linked
coordinated views have to work as expected for all supported
data types. A set should not be seen as a new arti cial data
type, that we have to convert existing data to, but as the
natural data type in many applications. Instead of
introducing another conversion step for our data, we can
avoid converting data with multiple related attributes to a
range of categorical dimensions. Using sets is also an
ecient way of dimension reduction, and can reduce the
complexity of a dataset, as well as the amount of views
needed for exploration. Additionally, there are some
examples on how to take advantage of sets when analyzing a
real-world dataset. Some special features of this dataset as
well as some erroneous entries are easier to nd by using
sets and views that support them.",
month = mar,
address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
school = "Institute of Computer Graphics and Algorithms, Vienna
University of Technology ",
URL = "https://www.cg.tuwien.ac.at/research/publications/2008/freiler-2008-ste/",
}