View source for In2vis

'''Title:''' Interactive Information Visualization (in2vis)<br>
'''Participants:''' [[Miksch, Silvia|Silvia Miksch]]<sup>1</sup>, [[Hinum, Klaus|Klaus Hinum]]<sup>1</sup>, [[Pohl, Margit|Margit Pohl]]<sup>2</sup>, [[Rester, Markus|Markus Rester]]<sup>2</sup>, Christian Popow<sup>3</sup>, Susanne Ohmann<sup>3</sup><br>
'''Institutions:''' 
#[[Information Engineering Group (ieg), Vienna University of Technology (TU Wien)|Information Engineering Group (ieg)]], Institute of Software Technology and Interactive System, Vienna University of Technology, Vienna, Austria, Europe.
#[http://igw.tuwien.ac.at/zope/igw/ HCI-group], Institute of Design and Assessment of Technology, Vienna University of Technology, Vienna, Austria, Europe.
#[http://www.meduniwien.ac.at/index.php?id=372&language=2 Medical University of Vienna], Vienna, Austria, Europe.<br>
'''Homepage:''' http://ieg.ifs.tuwien.ac.at/projects/in2vis/<br>

'''Description:''' Users are confronted with a huge amount of abstract, but highly structred data. They want to accomplish different kinds of tasks, where they need different interactions and navigations as well as different views of the same data to gain more insight into the data under investigation.  These processes of investigation are very complex and only little guidance exists. Therfore, our aims are
*to explore and to compare different methods (Information Visualization, Exploratory Data Analys and Machine Learning) to ease the understanding (the human reasoning process), to find their strengths and limitations and to estimate how combinations of these methods can contribute to more in-depth reasoning processes; and
*to develop guidelines how to explore and visualize data and information task- and user- appropriately.

To fullfill these aims we will conduct a study with medical data from the Department of Child and Adolescent Neuropsychiatry at the Medical University of Vienna. This highly structured, time based, categorical data comes from questionnaires of girls with eating disorders (anorexia nervosa).

A new exploratory information visualization named Gravi++ was developed in the course of the in2vis project as the information visualization method of the study. This method was designed for our medical data and is able to help the user analyse the data and predict further development of the patients. It uses the placement (with a spring based method) and animation of icons to display the data.

[[Category:Projects]]