Time-varying data is usually explored by animation or arrays of static images. Neither is
particularly effective for classifying data by different temporal activities. Important temporal …

Understanding the changes of time-series is a common task in many application domains.
Converting time-series data into videos helps an audience with little or no background …

This paper presents an approach for the interactive visualization, exploration and
interpretation of large multivariate time series. Interesting patterns in such datasets usually …

Time series are a data type of utmost importance in many domains such as business
management and service monitoring. We address the problem of visualizing large time …

Time‐series data is a common target for visual analytics, as they appear in a wide range of
application domains. Typical tasks in analyzing time‐series data include identifying cyclic …

Multiple time series are a set of multiple quantitative variables occurring at the same interval.
They are present in many domains such as medicine, finance, and manufacturing for …

Visual representations of time-series are useful for tasks such as identifying trends, patterns
and anomalies in the data. Many techniques have been devised to make these visual …

Providing appropriate methods to facilitate the analysis of time-oriented data is a key issue
in many application domains. In this paper, we focus on the unique role of the parameter …

We introduce time curves as a general approach for visualizing patterns of evolution in
temporal data. Examples of such patterns include slow and regular progressions, large …

Heatmap is one of the effective representations for time-varying data visualization. It may
require large display spaces when an input dataset contains large number of data items or …