Quantification of Visual Analytics Transformations and Mappings

Research Questions

  • How can we measure and quantify the quality of a visualization? In which way do methods in the data space differ from methods in the image space?
  • How can we compare the measured quality of a visualization with the perception of a human?
  • How can the user be involved into a quality-metric-driven process of visual mappings and transformations?
  • What is the influence of perceptual effects on quality measures?
  • Can we enhance the visual representation of information by introducing perceptual effects into visualizations?

Selected Results

SMARTexplore: A novel, table-based Visual Analytics approach to identify and understand clusters, correlations, and complex patterns in high-dimensional data. We use quality metrics for a semi-automatic reliability analysis and a pattern-based layout of rows and columns. Pattern matching and subspace analysis algorithms are used to reveal interesting findings. Try it out here.



Funding

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This research project received funding from the DFG (Deutsche Forschungsgemeinschaft) within the SFB-TRR 161.

Publications