Gravi++: Interactive Information Visualization to Explore Highly Structured Temporal Data

Klaus Hinum (Institute of Software Technology and Interactive Systems, Vienna University of Technology, Austria)

Silvia Miksch (Institute of Software Technology and Interactive Systems, Vienna University of Technology, Austria)

Wolfgang Aigner (Institute of Software Technology and Interactive Systems, Vienna University of Technology, Austria)

Susanne Ohmann (Department of Child and Adolescent Psychiatry, Medical University of Vienna, Austria)

Christian Popow (Department of Child and Adolescent Psychiatry, Medical University of Vienna, Austria)

Margit Pohl (Institute of Design and Assessment of Technology, Vienna University of Technology, Austria)

Markus Rester (Institute of Design and Assessment of Technology, Vienna University of Technology, Austria)

Abstract: Tracking and comparing psychotherapeutic data derived from questionnaires involves a number of highly structured, time-oriented parameters. Descriptive and other statistical methods are only suited for partial analysis. Therefore, we created a novel spring-based interactive Information Visualization method for analysing these data more in-depth. With our method the user is able to find new predictors for a positive or negative course of the therapy due to the combination of various visualization and interaction methods.

Keywords: interactive information visualization, medical domain, temporal data

Categories: H.3.3, H.5.1, J.3