Lesson01

From Visual Analytics and Applications
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Vaa.jpg ISSS608 Visual Analytics and Applications

About

Weekly Session

Assignments

Visual Analytics Project

Course Resources

 


Demystifying Visual Analytics

Lesson 1 slides

Content

Introduction to the course

  • Why this course?
  • What does it cover?
  • Who is involved?
  • What assignments?
  • Rules to be followed

Motivations of Visual Analytics

  • Massive data
  • Complex problem
  • Visual Representation
  • New visual paradigm
  • Hidden insight

The Visual Analytics Framework

  • The Science of Analytical Reasoning
  • Sense-Making Methods
  • Components of visual analytics
  • History of visual analytics
  • The visual analytics process
  • Application challenges
  • Technical challenges

A Gallery of Visual Analytics applications

Visualising and Analysing Univariate Data

  • Data discovery with bar chart
  • Data discovery with dotplot

Visualising and Analysing Bivariate Categorical Data

  • Exploring two categorical variables
  • Working with mosaic plot and trellis
  • Bivariate categorical data analysis best practices


Hands-on Session


Daily Readings

Day Time required Readings
Day 1 60 mins

The best stats you've ever seen [1]Must view!

A Tour through the Visualization Zoo [2]Must read!

Day 2 60 mins

Why Visual Analytics [3]Must view!

Andrew Gelman and Antony Unwin (2011) Infovis and Statistical Graphics: Different Goals, Different Looks [4]Must read!

Robert Kosara (2012) Visualization: It’s More than Pictures! [5]Must read!

Day 3 60 mins

Demystifying Visual Analytics, IEEE Computer Graphics and Applications, March/April 2009 e-journal @smu library Must read!

Visual Analytics - Mastering the Information Age [6]Must view!

Visual analysis for everyone [7]

Day 4 60 mins

Tools for Visualising [8]

The beauty of data visualization [9]Must view!

Data Visualisation, Australian Bureau of Statistics Research Paper, July 2007 [10]

Day 5 3 hours

Self-learning Tableau

  • Getting Started [11]
  • Tableau Interface [12]
  • Connecting to Data: From Getting Started with Data to Data Blending [13]

References

James J. Thomas & Kristin A. Cook (ed) (2005) Illuminating the Path: The Research and Development Agenda of Visual Analytics [14]


Discussion

Discussion Lesson 01