Interactive Poster: 3D Axes-Based Visualizations for Time Series Data

نویسندگان

  • Christian Tominski
  • James Abello
  • Heidrun Schumann
چکیده

In this work we present novel axes-based visualizations that can be used to explore and analyze multivariate time series data. We propose different types of interactive axes, which in turn can be used to compile novel 3D axes arrangements. The proposed axesbased visualizations utilize an exposed central time axis around which axes representing time-dependent attributes are arranged. Each depending attribute is visually associated with the time axis by means of different types of drawings.

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تاریخ انتشار 2005