Visualizing Dynamic Quantitative Data in Hierarchies

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Water level data visualization for German rivers

Dynamic quantitative data exists in a variety of forms and there have been many attempts to make this kind of data visible on screen with the goal to detect temporal patterns.

In this paper we introduce a technique for visualizing the dynamics of quantitative data in static hierarchical structures. We exploit the straight links of orthogonal tree diagrams as a timeline on which we visually encode dynamic quantitative information. We use color coding and varying thicknesses to represent the time-varying data. Bimodal data can also be displayed by exploiting both sides of the time axes simultaneously.

Water level data visualization for a part of the river Elbe

Our TimeEdgeTrees tool allows us to explore dynamic quantitative data in tree diagrams by interactive data filtering and zooming. The spatial proximity of neighboring hierarchically structured elements allows us to easily explore trends, countertrends, periodicity, temporal shifts, or anomalies during the evolution synchronously. Interactive features such as expanding or collapsing of subhierarchies additionally help to detect the aforementioned phenomena on different levels of granularity. The usefulness of our visualization technique is illustrated by water level data acquired at more than 450 measurement stations along German rivers for 768 points in time.