Abstract
We present a Visual Analytics approach that addresses the detection of interesting patterns in numerical time series, specifically from environmental sciences. Crucial for the detection of interesting temporal patterns are the time scale and the starting points one is looking at. Our approach makes no assumption about time scale and starting position of temporal patterns and consists of three main steps: an algorithm to compute statistical values for all possible time scales and starting positions of intervals, visual identification of potentially interesting patterns in a matrix visualization, and interactive exploration of detected patterns. We demonstrate the utility of this approach in two scientific scenarios and explain how it allowed scientists to gain new insight into the dynamics of environmental systems.
Highlights
Advancement of recent technology allows geoscientists to measure and to simulate a wide range of variables of environmental systems
We present a Visual Analytics approach that addresses the detection of interesting patterns in environmental time series
We propose a straightforward, yet significant, approach that captures characteristics of the temporal behavior of environmental systems across all possible time scales and starting positions of intervals based on a user-chosen statistical measure
Summary
Advancement of recent technology allows geoscientists to measure and to simulate a wide range of variables of environmental systems. The resulting environmental time series encompass long time periods at high (and sometimes varying) sampling rates. To study the temporal behavior of observed environmental systems, scientists need to detect interesting patterns in these time series. Since the dynamics of environmental systems are typically not completely understood, the detection of interesting patterns in environmental time series comprises two major challenges. Researchers often have difficulties to specify in advance what constitutes an ‘interesting’ pattern. The time scales on which interesting temporal patterns occur are often difficult to determine. Environmental systems show interesting patterns at very different time scales. A time scale denotes the length of intervals of a logical division of the time series
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