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 …

The need for pattern discovery in long time-series data led researchers to develop
interactive visualization tools and analytical algorithms for gaining insight into the data. Most …

Collecting sensor data results in large temporal data sets which need to be visualized,
analyzed, and presented. One-dimensional time-series charts are used, but these present …

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 …

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 …

For irregularly measured time-series data, the measurement frequency or interval is as
crucial information as measurements are. A well-known time-series visualization such as the …

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 …

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 …

Numeric time series is a class of data consisting of chronologically ordered observations
represented by numeric values. Much of the data in various domains, such as financial …