filename     : egws97_springer
title        : A Framework for Physically-Based Information Visualization
author       : T. C. Sprenger, M. H. Gross, A. Eggenberger, M. Kaufmann
type         : inbook
organisation : Institute for Information Systems, 
               Swiss Federal Institute of Technology, Zürich
month        : July 
year         : 1997
keywords     : information visualization, physically based model, clustering
language     : english
pages        : 14
abstract     :
 The following paper describes a framework for the visualization and analysis of economic data. It can be
 employed in the context of risk analysis, stock prediction and other tasks being important in the context of
 banking. The system bases on a quantification of the similarity of related objects, which governs the parameters
 of a mass-spring system, organized as two concentric spheres. More specifically, we initialize all information
 units onto the surface of the inner sphere and attach them with springs to the outer sphere. Since the spring
 stiffnesses correspond to the computed similarity measures, the system converges into an energy minimum,
 which reveals multidimensional relations and adjacencies in terms of spatial neighborhoods. In order to sim-plify
 complex setups we propose an additional clustering algorithm for postprocessing. Furthermore, depend-ing
 on the application scenario we support different topologic arrangements of related objects. In addition, we
 implemented various interaction techniques allowing semantic analysis of the underlying data sets. The versa-tility
 of our approach is illustrated by two examples, namely a comparison of agricultural productivity and an
 analysis of the relation between interest rates and other economic data.