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

• 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