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
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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
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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
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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
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13. Use of visualizations for research
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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
21. Agenda
• Introduction
• Interactive visualizations
• GBD visualizations: examples in a research setting
• The main steps for visualizing data
• Practical example
• Final questions
21
IntroExamplesTalk through GBD viz for usageLearnings from creating those: how to go aboutPractical examplesQ&A
Let’s start with the last points and work backwardsFew historic examples to provide some contextClear take-aways
Cholera on braod streetTheory: bad airCounting casesNo proof in waterPump handle
Pie chart with 12 slices for monthsArea (from middle) proportionate to deathsCommunicable disease bigger enemy than RussiansMilitary hospital system
Number of soldiersLocationDirectionDateTemperatureStories: river crowssing
Fast-forward over 100 yearsWeb allows interactivitySoftware allows watching movies of time trends, allows for integrating any indicatorTED visualizations
Bill Gates: big milestone after Rosling’sGapminder