La Trobe University: Visual Analytics (BUS5VA)

1. BUS5VA: Assignment 1
- Pradeep Poonia (19108160)
- Saharsh Parekh (19119324)
- Siddhanth Chaurasiya (19139507)

2. Research Paper: Framework for
Visualizing Research Data.
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• Introduction
• Visualisation Framework
• Effective Visualization: Homicide
case study
• Non-Effective Visualization: Radar
Plot in Sports Analytics
• References

3. Visualization Framework
• What is Framework ?
• Advantages and Disadvantages
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4. Framework Process
Elements of Framework:
• Data Description
• Feature Engineering
• Software Selection
• Dissemination
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Problem Statement:
Experimental program in the field of
education
Solutions:
Timely accessibility
Interaction

5. Visualization Products
▪ Distribution of Interactions
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6. Visualization Products
▪ Network map of Top Institutions:
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7. Visualization Products
▪ Enrolment in Selective Institutions:
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8. Future Work
• Unique properties of other datasets .
• Difficulty – Usage of R and certain component.
• Bypass - Peer-review process.
• Not tested Enough
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9. Learnings
• A picture is worth a
thousand words?
• Meaningful picture
visualization
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10. Effective Visualization:
Visualisation Tool and
Techniques
▫ Pictorial Representation
▪ Line Chart
▪ Doughnut chart Vs Pie Chart
▪ Lollipop Chart
▪ Bar Chart
▪ Percent Total Victim to Family
Homicide Ratio
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11. 11
Tabular Vs Pictorial
Saharsh Parekh: 19119324

12. 12
Effective use of Geo-spatial with Pie-chart
Saharsh Parekh: 19119324

13. 13
Effective Use of Stacked Chart
▪ Female
▪ Male
▪ Region
▪ Intimate Partner
related Homicide
▪ Other Homicides
▪ Unknown
Saharsh Parekh: 19119324

14. 14
Interactive Tool -
https://homicide.igarape.org.br/
Case Study -
▪ Periscopic Tool – Analytical representation of Data
▪ PIWIK Tool – Geographic Representation of data
▪ PHP – Web based Designing
▪ MySql – Data collection
Saharsh Parekh: 19119324

15. Non-Effective Visualization:
Radar Plots
▫ Application
▪ Issue
▪ Alternative
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16. Application
• Used widely in Football and
Basketball.
• Scouting, Performance
metric & Player evaluation.
• Novel, Aesthetically
pleasing and allows multiple
attribute comparison.
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17. Issues
• Independent Scales
• Variable ordering
• Interpretation
• Mislead
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18. Alternative
Parallel Coordinates:
• Different Axis Scales
• No distortion
• Easy to interpret
• Compare multiple entities
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19. References
▪ Research Paper (A framework for visualizing research data):
http://ieeexplore.ieee.org.ez.library.latrobe.edu.au/document/793
7748/
▪ Case Study: Effective Visualization.
http://www.unodc.org/documents/gsh/pdfs/2014_GLOBAL_HO
MICIDE_BOOK_web.pdf
▪ Case Study: Non-Effective Visualization.
Sam Ventura (@Stat_Sam)
http://statsbomb.com/2016/04/understand-football-radars-for-
mugs-and-muggles/
▪ http://sirvizalot.blogspot.com.au/2016/10/espns-all-time-nba-
ranks.html
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20. THANKS!
Any questions?
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