Difference between revisions of "Lesson01"
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| + | <Font size =5>'''Introduction to Visual Analytics'''</font> | ||
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| + | <font size = 3>[[Media:ISSS608_Lesson01-v1.3.1.pdf|Lesson 1 slides]]</font> | ||
| + | |||
| + | == 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</font> | ||
| + | * Exploring two categorical variables | ||
| + | * Working with mosaic plot and trellis | ||
| + | * Bivariate categorical data analysis best practices | ||
| + | |||
| + | |||
| + | == Hands-on Session == | ||
| + | |||
| + | Self-learning Tableau | ||
| + | * Getting Started [http://www.tableau.com/learn/tutorials/on-demand/getting-started] | ||
| + | * Tableau Interface [http://www.tableau.com/learn/tutorials/on-demand/tableau-interface] | ||
| + | * Connecting to Data: From Getting Started with Data to Data Blending | ||
| + | |||
| + | |||
| + | == Daily Readings == | ||
| + | |||
| + | {| border="1" cellpadding="1" | ||
| + | |- | ||
| + | |width="5pt"|Day | ||
| + | |width="10pt"|Time required | ||
| + | |width="350pt"|Readings | ||
| + | |- | ||
| + | |Monday||60 mins|| | ||
| + | The best stats you've ever seen [http://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen]'''Must view!''' | ||
| + | |||
| + | A Tour through the Visualization Zoo [http://queue.acm.org/detail.cfm?id=1805128]'''Must read!''' | ||
| + | |||
| + | |- | ||
| + | |- | ||
| + | |Tuesday||60 mins|| | ||
| + | Why Visual Analytics [http://www.youtube.com/watch?v=5uGRGqCFryg]'''Must view!''' | ||
| + | |||
| + | Andrew Gelman and Antony Unwin (2011) Infovis and Statistical Graphics: Different Goals, Different Looks [http://www.stat.columbia.edu/~gelman/research/published/vis14.pdf]'''Must read!''' | ||
| + | |||
| + | Robert Kosara (2012) Visualization: It’s More than Pictures! [http://stat-computing.org/newsletter/issues/scgn-22-1.pdf]'''Must read!''' | ||
| + | |||
| + | |- | ||
| + | |||
| + | |Wednesday||3hrs|| | ||
| + | |||
| + | Lesson 01 | ||
| + | |||
| + | * In-class hands-on exercise 01 | ||
| + | |||
| + | |||
| + | |- | ||
| + | |Thursday||60 mins|| | ||
| + | Demystifying Visual Analytics, ''IEEE Computer Graphics and Applications, March/April 2009'' e-journal @smu library '''Must read!''' | ||
| + | |||
| + | The beauty of data visualization [http://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization.html]'''Must view!''' | ||
| + | |||
| + | Tools for Visualising [http://www.visualisingdata.com/index.php/resources/] | ||
| + | |||
| + | Visual analysis for everyone [http://www.tableausoftware.com/whitepapers/visual-analysis-everyone] | ||
| + | |||
| + | |- | ||
| + | |||
| + | |Friday||60 mins|| | ||
| + | Visual Analytics - Mastering the Information Age [http://www.youtube.com/watch?v=5i3xbitEVfs]'''Must view!''' | ||
| + | |||
| + | Data Visualisation, Australian Bureau of Statistics Research Paper, July 2007 [http://www.abs.gov.au/ausstats/abs@.nsf/mf/1211.0.55.001] | ||
| + | |- | ||
| + | |- | ||
| + | |- | ||
| + | |} | ||
| + | |||
| + | |||
| + | == References == | ||
| + | James J. Thomas & Kristin A. Cook (ed) (2005) Illuminating the Path: The Research and Development Agenda of Visual Analytics [http://vis.pnnl.gov/pdf/RD_Agenda_VisualAnalytics.pdf] | ||
| + | |||
| + | |||
| + | == Discussion == | ||
| + | |||
| + | [[Talk:Lesson01|Discussion Lesson 01]] | ||
Revision as of 00:46, 9 August 2016
ISSS608 Visual Analytics and Applications
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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
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
Self-learning Tableau
- Getting Started [1]
- Tableau Interface [2]
- Connecting to Data: From Getting Started with Data to Data Blending
Daily Readings
| Day | Time required | Readings |
| Monday | 60 mins |
The best stats you've ever seen [3]Must view! A Tour through the Visualization Zoo [4]Must read! |
| Tuesday | 60 mins |
Why Visual Analytics [5]Must view! Andrew Gelman and Antony Unwin (2011) Infovis and Statistical Graphics: Different Goals, Different Looks [6]Must read! Robert Kosara (2012) Visualization: It’s More than Pictures! [7]Must read! |
| Wednesday | 3hrs |
Lesson 01
|
| Thursday | 60 mins |
Demystifying Visual Analytics, IEEE Computer Graphics and Applications, March/April 2009 e-journal @smu library Must read! The beauty of data visualization [8]Must view! Tools for Visualising [9] Visual analysis for everyone [10] |
| Friday | 60 mins |
Visual Analytics - Mastering the Information Age [11]Must view! Data Visualisation, Australian Bureau of Statistics Research Paper, July 2007 [12] |
References
James J. Thomas & Kristin A. Cook (ed) (2005) Illuminating the Path: The Research and Development Agenda of Visual Analytics [13]
