VISUALIZATION METHODS FOR TIME-DEPENDENT DATA-AN OVERVIEW

Visualization has been successfully applied to analyse time-dependent data for a long time now. Lately, a number of new approaches have been introduced, promising more effective graphs especially for large datasets and multiparameter data. In this paper, we give an overview on the visualization of time-series data and the available techniques. We provide a taxonomy and discuss general aspects of time-dependent data. After an overview on conventional techniques we discuss techniques for analysing time-dependent multivariate data sets in more detail. After this, we give an overview on dynamic presentation techniques and event-based visualization. 1 MOTIVATION AND BACKGROUND The analysis of time-series data is one of the most widely appearing problems in science, engineering, and business. In the last years this problem gained increasing importance due to the fact that more sensitive sensors in science and engineering and the widespread use of computers in corporations have increased the amount of time-series data collected by many magnitudes. For long, visualization has proven to be an effective approach to analyze time-series data. The motivation behind this approach is to exploit the phenomenal abilities of the human eye to detect structures in images. A well designed visualization can aid in answering the following questions for unknown temporal data (MacEachren 1995):

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