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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.

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review visual methods for analyzing time oriented data

Review: Visual Methods for Analyzing Time-Oriented Data

Authors: Wolfgang Aigner, Silvia Miksch, Wolfgang Mu¨ ller, Heidrun Schumann, and Christian Tominski

introduction
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
Types of Times
  • Linear Time vs Cyclic Time
  • Time Points vs Time Intervals
  • Ordered Time vs Branching Time vs Time with multiple perspectives
ordertime
OrderTime
  • ThemeRiver
branching time and time with multiple perspectives
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
Analyzing Time Oriented Data
  • Temporal Data Abstraction
  • Principal Component Analysis
  • Clustering
temporal data abstraction
Temporal Data Abstraction
  • VIE_VENT’s schema
  • Knowledge on data
  • Context Sensitive
  • Expectation guided
  • Quant to Qualitative
temporal data abstraction1
Temporal Data Abstraction
  • The Spread Visualization - Oscillating Data
principal component based analysis
Principal Component Based Analysis
  • Dimensionality reduction technique
  • Finding dimensions with maximum variance
  • Transforming original dataset to different domain
slide13
PCA
  • Themeriver
slide14
PCA
  • Bar chart visualization of one component
clustering
Clustering
  • Calendar metophar
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