Towards closing the analysis gap: visual generation of decision supporting schemes from raw data
EuroVis'08 Proceedings of the 10th Joint Eurographics / IEEE - VGTC conference on Visualization
| Hi-index | 0.00 |
We present an interactive visualization method for the multivariate analysis of large and complex datasets, based on the layout of Karnaugh-Veitch-diagrams. Working on data categories, we additionally provide an interactive partitioning of value ranges of ordinal types. Multivariate dependencies manifest on the map in characteristic color patterns. These patterns are representations of subsets of the data or attributes which embody significant information. While the task of the user is to identify visual patterns of particular interest to him by clicking on the map, the software identifies a minimal representation of the corresponding subset and gives a visual feedback. Hence, user and machine cooperate on the basis of a strong visual coupling in short iterative cycles. During this process the trade-off between the accuracy and simplicity of a representation, which is crucial for any type of the building of analytical models, can be found in an effective way.