Review: Visual Methods for
Analyzing Time-Oriented Data
Authors: Wolfgang Aigner, Silvia
Miksch, Wolfgang Mu¨ ller, Heidrun
Schumann, and Christian Tominski
Introduction
• This paper presents visualization techniques
for various types of temporal data.
• Large amount of data – requires human
analysis and decision making
• Aspects of visualizing temporal data
– Visualization, analysis and user
• Time characteristics must be considered while
visualizing temporal data
• Appropriate parameterization and interaction
Types of Times
• Linear Time vs Cyclic Time
• Time Points vs Time Intervals
• Ordered Time vs Branching Time vs Time with
multiple perspectives
Linear Time vs Cyclic Time
Time Points vs Time Intervals
• Time Wheel
Time Points vs Time Intervals
• PlanningLines
OrderTime
• ThemeRiver
Branching Time and Time with
multiple Perspectives
• Not many effective tools to visualize such data
• Mostly ordered data visualization or univariate
visualization - planninglines
Analyzing Time Oriented Data
• Temporal Data Abstraction
• Principal Component Analysis
• Clustering
Temporal Data Abstraction
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VIE_VENT’s schema
Knowledge on data
Context Sensitive
Expectation guided
Quant to Qualitative
Temporal Data Abstraction
• The Spread Visualization - Oscillating Data
Principal Component Based Analysis
• Dimensionality reduction technique
• Finding dimensions with maximum variance
• Transforming original dataset to different
domain
PCA
• Themeriver
PCA
• Bar chart visualization of one component
Clustering
• Calendar metophar
Clustering
User centered analysis via Events