Similarity-Based Visualization of Time Series Collections: An Application to Analysis of Streamflows

Time series analysis poses many challenges to professionals in a wide range of domains. Several visualization solutions have been proposed for exploratory tasks on time series collections. For large data sets, however, current techniques fail to provide a global view that supports a good association between groups of similar time series. We employ fast multidimensional projection techniques to create concise visual representations of a collection of time series. The whole collection can be viewed in a two-dimensional graph-based representation that provides a starting point for further exploration and detailed analysis. The projections employ distance metrics to compare the series and generate a layout that attempts to group those with similar behavior. We illustrate the approach on a real data set containing streamflows describing the behavior of hydroelectric power plants in Brazil.

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