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UNIVERSITY OF WASHINGTON
Data visualization workshop
Peter Speyer Kyle Foreman
Director of Data Development PhD Candidate
IHME Imperial CollegeJune 18, 2013
Agenda
• Introduction
• Interactive visualizations
• GBD visualizations: examples in a research setting
• The main steps for visualizing data
• Practical example
• Final questions
2
Why do we visualize data?
Review data
• Make sense of large amounts
of data
• Explore patterns and trends
• Evaluate research results
• Find stories
Communicate results
• Make data engaging
• Cut through the clutter
• Let users explore the data
• Use for presentations
• Tell stories
3
4John Snow’s map of cholera cases in London, 1854
5Florence Nightingale, Deaths on Crimean Peninsula, 1858
6Charles Joseph Minard’s map of Napoleon’s Russian campaign of 1812, published 1869
7Gapminder World, http://www.gapminder.org, founded 2005
8
“People are generally better persuaded
by the reasons
which they have themselves discovered
than by those
which have come into the mind of others”
Blaise Pascal
9
Agenda
• Introduction
• Interactive visualizations
• GBD visualizations: examples in a research setting
• The main steps for visualizing data
• Practical example
• Final questions
10
Agenda
• Introduction
• Interactive visualizations
• GBD visualizations: examples in a research setting
• The main steps for visualizing data
• Practical example
• Final questions
11
Global Burden of Disease 2010 - Results
291 causes / 4 hierarchical levels
67 risk factors / 2 levels
21 age groups (3 infant age groups, 1-4, 5-9 … 75-79, 80+)
Female/male/both
187 countries
1990, 2005, 2010
4 key metrics (deaths, YLLs, YLDs, DALYs)
Uncertainty bounds
12
Use of visualizations for research
13
Improving the
research work flow:
Mortality Visualization
COD Visualization
Review results:
GBD Compare
Share results & tell
stories:
GBD Cause Patterns
GBD Arrow Diagrams
Evaluating policy
impact:
Benchmarking tool
Agenda
• Introduction
• Interactive visualizations
• GBD visualizations: examples in a research setting
• The main steps for visualizing data
• Practical example
• Final questions
14
Be clear about your objectives
• What do I want to do / communicate?
• Am I telling a story or letting users
explore?
• What is my audience? How much do
they know about the topic? About
statistics? About visualizations?
15HikingArtist via Flickr
Prepare the data
• Identify all relevant available data
• Become intimate with your dataset(s):
metrics, units, dimensions, uncertainty
• Prepare data: Excel, Google Refine,
Data Wrangler, AP’s Overview
16Kikishua via Flickr
Build it
• Select the right type of visual
– Highlight your point
– Keep it simple
• Select the degree of interactivity
• Select the right visualization tool:
start simple
– Excel
– Public tools: Google Motion Charts,
Tableau Public, ArcGIS.com
– Custom coding: D3.js, Highcharts
– Maps: visualization vs. GIS
17Edwc via Flickr
Final thoughts
• Facilitate viral communication
– Permalinks
– Social media integration
– Embedding visualizations
– Download screenshot
• Working with software developers
– Requirements
– Testing
– Documentation
– Priorities
18ocean.flynn via Flickr
How do I know if I succeeded?
19Mr. Aktugan via Flickr
Further reading & inspiration
• http://flowingdata.com/
• http://blog.visual.ly/
• http://www.informationisbeautiful.net/
• http://www.visualcomplexity.com/vc/
• http://visualization.geblogs.com/
• http://eagereyes.org/
• http://chartporn.org/
• http://worldbank.tumblr.com/
20
Agenda
• Introduction
• Interactive visualizations
• GBD visualizations: examples in a research setting
• The main steps for visualizing data
• Practical example
• Final questions
21
Questions?
speyer@uw.edu
kyleforeman@gmail.com
http://ihmeuw.org/gbd
22

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Data Visualization Workshop at GHME

  • 1. UNIVERSITY OF WASHINGTON Data visualization workshop Peter Speyer Kyle Foreman Director of Data Development PhD Candidate IHME Imperial CollegeJune 18, 2013
  • 2. Agenda • Introduction • Interactive visualizations • GBD visualizations: examples in a research setting • The main steps for visualizing data • Practical example • Final questions 2
  • 3. Why do we visualize data? Review data • Make sense of large amounts of data • Explore patterns and trends • Evaluate research results • Find stories Communicate results • Make data engaging • Cut through the clutter • Let users explore the data • Use for presentations • Tell stories 3
  • 4. 4John Snow’s map of cholera cases in London, 1854
  • 5. 5Florence Nightingale, Deaths on Crimean Peninsula, 1858
  • 6. 6Charles Joseph Minard’s map of Napoleon’s Russian campaign of 1812, published 1869
  • 8. 8
  • 9. “People are generally better persuaded by the reasons which they have themselves discovered than by those which have come into the mind of others” Blaise Pascal 9
  • 10. Agenda • Introduction • Interactive visualizations • GBD visualizations: examples in a research setting • The main steps for visualizing data • Practical example • Final questions 10
  • 11. Agenda • Introduction • Interactive visualizations • GBD visualizations: examples in a research setting • The main steps for visualizing data • Practical example • Final questions 11
  • 12. Global Burden of Disease 2010 - Results 291 causes / 4 hierarchical levels 67 risk factors / 2 levels 21 age groups (3 infant age groups, 1-4, 5-9 … 75-79, 80+) Female/male/both 187 countries 1990, 2005, 2010 4 key metrics (deaths, YLLs, YLDs, DALYs) Uncertainty bounds 12
  • 13. Use of visualizations for research 13 Improving the research work flow: Mortality Visualization COD Visualization Review results: GBD Compare Share results & tell stories: GBD Cause Patterns GBD Arrow Diagrams Evaluating policy impact: Benchmarking tool
  • 14. Agenda • Introduction • Interactive visualizations • GBD visualizations: examples in a research setting • The main steps for visualizing data • Practical example • Final questions 14
  • 15. Be clear about your objectives • What do I want to do / communicate? • Am I telling a story or letting users explore? • What is my audience? How much do they know about the topic? About statistics? About visualizations? 15HikingArtist via Flickr
  • 16. Prepare the data • Identify all relevant available data • Become intimate with your dataset(s): metrics, units, dimensions, uncertainty • Prepare data: Excel, Google Refine, Data Wrangler, AP’s Overview 16Kikishua via Flickr
  • 17. Build it • Select the right type of visual – Highlight your point – Keep it simple • Select the degree of interactivity • Select the right visualization tool: start simple – Excel – Public tools: Google Motion Charts, Tableau Public, ArcGIS.com – Custom coding: D3.js, Highcharts – Maps: visualization vs. GIS 17Edwc via Flickr
  • 18. Final thoughts • Facilitate viral communication – Permalinks – Social media integration – Embedding visualizations – Download screenshot • Working with software developers – Requirements – Testing – Documentation – Priorities 18ocean.flynn via Flickr
  • 19. How do I know if I succeeded? 19Mr. Aktugan via Flickr
  • 20. Further reading & inspiration • http://flowingdata.com/ • http://blog.visual.ly/ • http://www.informationisbeautiful.net/ • http://www.visualcomplexity.com/vc/ • http://visualization.geblogs.com/ • http://eagereyes.org/ • http://chartporn.org/ • http://worldbank.tumblr.com/ 20
  • 21. Agenda • Introduction • Interactive visualizations • GBD visualizations: examples in a research setting • The main steps for visualizing data • Practical example • Final questions 21

Notas do Editor

  1. IntroExamplesTalk through GBD viz for usageLearnings from creating those: how to go aboutPractical examplesQ&A
  2. Let’s start with the last points and work backwardsFew historic examples to provide some contextClear take-aways
  3. Cholera on braod streetTheory: bad airCounting casesNo proof in waterPump handle
  4. Pie chart with 12 slices for monthsArea (from middle) proportionate to deathsCommunicable disease bigger enemy than RussiansMilitary hospital system
  5. Number of soldiersLocationDirectionDateTemperatureStories: river crowssing
  6. Fast-forward over 100 yearsWeb allows interactivitySoftware allows watching movies of time trends, allows for integrating any indicatorTED visualizations
  7. Bill Gates: big milestone after Rosling’sGapminder