HorizonVis – Interactive Visual Exploration of Multivariate Medical Measurements in Diabetes Care

  • Wolfgang Aigner, Vienna University of Technology
  • Michael Atanasov, HTBL Krems
  • Alexander Rind, Vienna University of Technology
  • Philipp Schindler, HTBL Krems
  • Reinhardt Wenzina, HTBL Krems

This project was funded by the Sparkling Science initiative of the Federal Ministry of Science and Research. HorizonVis was awarded € 5000 for a top 5 submissions to the third call.


Multivariate, time-oriented data plays a central role in many domains such as medicine, finance, or environmental engineering. Information Visualization can be an instrument to make such vast datasets intuitively comprehensible. As the number of time series increases, visualizations need to be space-efficient. Horizon graphs [Reijner, 2008] are an innovative approach to reduce required space by dividing the a chart into bands and layering these. While a first evaluation [Heer, et al., 2009] shows promising results, there is still room for optimization, especially regarding interaction techniques.

In the project HorizonVis, we implemented the horizon graph as component for the VisuExplore framework. HorizonVis was tested with the diabetes dataset from the UCI Machine Learning Repository. In order to support flexible usage, it provides several customization settings:

  • indexing values relative to a specific indexing point versus absolute values
  • number of bands [Heer, et al., 2009]
  • spread of a band, base value
  • mirroring versus offset for values below the base value [Heer, et al., 2009]
  • linear interpolation versus step chart
  • different color schemes
  • showing a legend [Saito et al., 2005]

Future work includes evaluation of HorizonVis in application scenarios (e.g., diabetes care). The applicability of indexing is of special interest. Furthermore, we plan to extend HorizonVis with advanced interaction techniques.

Related Work:

Alternative Webpages:

official project description (in German)