The display of multivariate datasets in parallel coordinates, transforms the search for relations among the variables into a 2-D pattern recognition problem. This is the basis for the application to visual data mining. The knowledge discovery process together with some general guidelines are illustrated on a dataset from the production of a VLSI chip. The special strength of parallel coordinates is in modeling relations. As an example, a simplified economic model is constructed with data from various economic sectors of a real country. The visual model shows the interelationship and dependencies between the sectors, circumstances where there is competition for the same resource, and feasible economic policies. Interactively, the model can be used to do trade-off analyses, discover sensitivities, do approximate optimization, monitor (as in a process) and provide decision support.
Index Terms:
data visualisation; multidimensional detective; multivariate dataset display; parallel coordinates; 2D pattern recognition problem; visual data mining; knowledge discovery; VLSI chip; modeling relations; economic model; economic sectors; competition; economic policies; trade-off analyses; approximate optimization; monitoring; decision support
Citation:
A. Inselberg, "Multidimensional detective," infovis, pp.100, 1997 IEEE Symposium on Information Visualization (InfoVis '97), 1997