Importance-Driven Visualization Layouts for Large Time Series Data

Time series are an important type of data with applications in virtually every aspect of the real world. Often a large number of time series have to be monitored and analyzed in parallel. Sets of time series may show intrinsic hierarchical relationships and varying degrees of importance among the individual time series. Effective techniques for visually analyzing large sets of time series should encode the relative importance and hierarchical ordering of the time series data by size and position, and should also provide a high degree of regularity in order to support comparability by the analyst. In this paper, we present a framework for visualizing large sets of time series. Based on the notion of inter time series importance relationships, we define a set of objective functions that space-filling layout schemes for time series data should obey. We develop an efficient algorithm addressing the identified problems by generating layouts that reflect hierarchyand importance-based relati...

• Type: Conference
• Year: 2005
• Where: INFOVIS
• Authors: Ming C. Hao, Umeshwar Dayal, Daniel A. Keim, Tobias Schreck
• Keywords: Individual Time Series, INFOVIS 2005, Time Series, Time Series Data, Visualization