Measuring Insight into Multi-dimensional Data from a Combination of a Scatterplot Matrix and a HyperSlice Visualization

  • André Calero ValdezEmail author
  • Sascha Gebhardt
  • Torsten W. Kuhlen
  • Martina Ziefle
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10287)


Understanding multi-dimensional data and in particular multi-dimensional dependencies is hard. Information visualization can help to understand this type of data. Still, the problem of how users gain insights from such visualizations is not well understood. Both the visualizations and the users play a role in understanding the data. In a case study, using both, a scatterplot matrix and a HyperSlice with six-dimensional data, we asked 16 participants to think aloud and measured insights during the process of analyzing the data. The amount of insights was strongly correlated with spatial abilities. Interestingly, all users were able to complete an optimization task independently of self-reported understanding of the data.


Information visualization Insight Multi-dimensional visualization Scatterplot HyperSlice Evaluation 



The authors thank the German Research Council DFG for the friendly support of the research in the excellence cluster “Integrative Production Technology in High Wage Countries”. We also thank Saskia De Luca for conducting the experiments.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • André Calero Valdez
    • 1
    Email author
  • Sascha Gebhardt
    • 2
  • Torsten W. Kuhlen
    • 2
  • Martina Ziefle
    • 1
  1. 1.Human-Computer Interaction CenterRWTH Aachen UniversityAachenGermany
  2. 2.Virtual Reality GroupRWTH Aachen UniversityAachenGermany

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