Lesson01

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Introduction to Visual Analytics


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


Hands-on Session

Visual Analytics for Business Intelligence Workbook version 1.0

  • Getting started with JMP
  • Visualising and analysing univariate data


Daily Readings

Day Time required Readings
Monday 30 mins Why Visual Analytics [1]Must view!

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

The beauty of data visualization [3]

Tuesday 30 mins

Visual analysis for everyone [4]

Visual Analytics - Mastering the Information Age [5]

Wednesday 30 mins Demystifying Visual Analytics, IEEE Computer Graphics and Applications, March/April 2009 e-journal @smu library

Tools for Visualising [6]

Data Visualisation, Australian Bureau of Statistics Research Paper, July 2007 [7]

Thursday 3 hours Lesson discussion and hands-on exercise
Friday 30 mins

Andrew Gelman and Antony Unwin (2011) Infovis and Statistical Graphics: Different Goals, Different Looks [8]

Robert Kosara (2012) Visualization: It’s More than Pictures! [9]


References

James J. Thomas & Kristin A. Cook (ed) (2005) Illuminating the Path: The Research and Development Agenda of Visual Analytics [10]