Exhaustive visual search for information in multi-dimensional data sets

Applicant:

Professor Dr.-Ing. Marcus Andreas Magnor, Braunschweig
Technische Universität Carolo-Wilhelmina zu Braunschweig
Carl-Friedrich-Gauß-Fakultät
Institut für Computergraphik

Professor Dr. Holger Theisel, Magdeburg
Otto-von-Guericke-Universität Magdeburg
Institut für Simulation und Graphik

Project:

Exhaustive visual search for information in multi-dimensional data sets (Publications)

Summary: 

Goal of this research project is to develop and evaluate a fundamentally new approach to exhaustively search for, and interactively characterize any non-random mutual relationship between attribute dimensions in general data sets. To be able to systematically consider all possible attribute combinations, we propose to apply image analysis to visualization results in order to automatically pre-select only those attribute combinations featuring non-random relationships. To characterize the found information and to build mathematical descriptions, we rely on interactive visual inspection and visualization-assisted interactive information modeling. This way, we intend to discover and explicitly characterize all information implicitly represented in unbiased sets of multi-dimensional data points.
Presentations: