Multiple View Framework for Highly Structured Data
LinkVis - Linking Visualization
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At the Department of Child and AdolescentNeuropsychiatry, Medical University of Vienna, apsychotherapeutic study is taking place, wherealternative (cognitive behavioural) therapeuticprocesses of anorectic girls are analysed. Within that study ahuge amount of time-oriented data is collected, which need to be synchronized according to differentconstraints to be comparable. Classical statistical methods are not applicable inthe absence of concrete hypotheses and can hardly capture the complex process of therapeuticinterventions. In this master thesis a multiple view framework witha powerful data ...
At the Department of Child and Adolescent
Neuropsychiatry, Medical University of Vienna, a
psychotherapeutic study is taking place, where
alternative (cognitive behavioural) therapeuticprocesses
of anorectic girls are analysed. Within that study a
huge amount of time-oriented data is collected,
which need to be synchronized according to different
constraints to be comparable.
Classical statistical methods are not applicable in
the absence of concrete hypotheses and can
hardly capture the complex process of therapeutic
interventions.
In this master thesis a multiple view framework with
a powerful data preprocessing part is designed.
The data preparation provides filtering, aggregation
of values with functions and the conflation of
records with different dates of measurement. The
framework is implemented in a tool called LinkVis
which visualizes the data with Chernoff faces, scatter
plots and parallel coordinates.
The scenario-based evaluation demonstrates the power
of the LinkVis tool on real world problems
and shows the data complexity. The tool is still a
prototype and it needs further improvements.
Neuropsychiatry, Medical University of Vienna, a
psychotherapeutic study is taking place, where
alternative (cognitive behavioural) therapeuticprocesses
of anorectic girls are analysed. Within that study a
huge amount of time-oriented data is collected,
which need to be synchronized according to different
constraints to be comparable.
Classical statistical methods are not applicable in
the absence of concrete hypotheses and can
hardly capture the complex process of therapeutic
interventions.
In this master thesis a multiple view framework with
a powerful data preprocessing part is designed.
The data preparation provides filtering, aggregation
of values with functions and the conflation of
records with different dates of measurement. The
framework is implemented in a tool called LinkVis
which visualizes the data with Chernoff faces, scatter
plots and parallel coordinates.
The scenario-based evaluation demonstrates the power
of the LinkVis tool on real world problems
and shows the data complexity. The tool is still a
prototype and it needs further improvements.
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