JUCS - Journal of Universal Computer Science 11(11): 1792-1805, doi: 10.3217/jucs-011-11-1792
Gravi++: Interactive Information Visualization to Explore Highly Structured Temporal Data
expand article infoKlaus Hinum, Silvia Miksch, Wolfgang Aigner, Susanne Ohmann§, Christian Popow§, Margit Pohl|, Markus Rester
‡ Institute of Software Technology and Interactive Systems, Vienna University of Technology, Austria§ Department of Child and Adolescent Psychiatry, Medical University of Vienna, Austria| Institute of Design and Assessment of Technology, Vienna University of Technology, Austria¶ Vienna University of Technology, Vienna, Austria
Open Access
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.
interactive information visualization, temporal data, medical domain