Set Type Enabled Information Visualization

Wolfgang Freiler
Set Type Enabled Information Visualization
[image] [paper]

Information

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.

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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 dierent data. These tools
               are made to handle dierent 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 9-11/186, 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/",
}