Eager to see big data techniques put to work solving difficult societal issues? During this workshop Datakind Dublin will demonstrate how lifeloggers have used their powerful data for the good of humankind. Datakind Dublin will share their international experiences as well as work done at home in Ireland. 'We are living inside a data revolution that is transforming the way we understand and interact with each other and the world, and it has only just begun' - DataKind Dublin launched in August 2014.

1. DataKind Dublin
Science Gallery, 17 April 2015
@DataKindDUB
#data4good

2. Welcome!
Today we are aiming to:
• Tell you a little bit about using Data for Social Good
• Show you interesting work of data used for social causes
• Help you explore some interesting visualizations
3pm to 5pm
meetup.com/DataKind-DUB/
dublin@datakind.org
@DataKindDUB
Great to have you here!

3. Welcome!
Website: sciencegallery20150417.pen.io
3pm to 5pm
meetup.com/DataKind-DUB/
dublin@datakind.org
@DataKindDUB
Great to have you here!

4. The power of Data
• HEALTH
• EDUCATION
• POLITICS
• DEVELOPMENT
...
• DAILY LIFE!

5. Good Data Science
First principles...
• Correlation doesn’t imply Causation
• Occam’s Razor
Communicating your results...
• Know your Audience
• Let the data tell the story
• ‘Intelligent Grandmother test’

6. Viz #1 Nigerian Sectarianism
Where did the data come from?
● Sourced from multiple International Agencies
○ UNHCR / OCHA
○ Integrated Regional Information Networks
How was the data visualisation put together?
● Al Jazeera journalists and developers created an
interactive visual narrative
Why is it interesting?
● Catalogs a complex and long running political
and paramilitary crisis in an interactive format
http://webapps.aljazeera.net/aje/custom/2014/bokoharamtimeline/index.html
Al Jazeera - Boko Haram’s Legacy

7. Viz #1 Nigerian Sectarianism
● What happened on August 26th 2011?
● When was the first case of internal displacement in Southern Nigeria?
● On the 50th anniversary of Nigerian Independence, there were attacks
in Abuja. Where in the capital did these take place?
For the eager ones!
● When is the first case of External Displacement and what caused it?
http://webapps.aljazeera.net/aje/custom/2014/bokoharamtimeline/index.html
Things to find...

8. Viz #2 - Selfie Analytics
Where did the data come from?
● Publicly Available Instagram Selfies
How was the Data Visualisation put together?
● Human Image Processing of Instagram Selfies
● Used Crowdsourcing to Classify Images - Amazon's Mechanical Turk
Why is it interesting?
● Study into passive LifeLogging by Instagram users
http://selfiecity.net/selfiexploratory
Beauty is in the Eye of the App-Holder

9. Viz #2 - Selfie Analytics
● Find all the girls in Sao Paulo with their Mouths Closed
● Find all the men in Bangkok who are looking up with their Eyes Open
● Find all the people who are Calm and Happy, then try Crop & Rotate
For the eager ones!
● Correlate people’s Mood with whether their Eyes are Open or Closed
http://selfiecity.net/selfiexploratory
Things to find...

10. Viz #3 - Prevalence of Diabetes
Where did the data come from?
● International Diabetes Federation’s Global Atlas (public data portal)
How was the Data Visualisation put together?
● IDF compiles data from
○ Peer-reviewed Journals
○ National Health Statistics Reports
○ International Agencies (CDC, WHO, …)
Why is it interesting?
● Independent analysis of Global Diabetes Data
● Find out potential new answers to pressing questions
https://public.tableau.com/s/gallery/prevalence-diabetes-world
Diabetes Mellitus - The Silent Epidemic

11. Viz #3 - Prevalence of Diabetes
● What is the prevalence of diabetes in your country? How does it
compare to the surrounding region and the world overall?
● Which countries have the highest diabetes prevalence? Can you find
any connection between them?
● Pick a region (Europe, Asia etc) of your interest and find out what are
the countries with the highest and lowest levels of diabetes.
For the eager ones!
● Explore the relationship between diabetes and IGT (impaired glucose
tolerance). Do you think they are related?
https://public.tableau.com/s/gallery/prevalence-diabetes-world
Things to find...

12. Viz #4 - Educating Girls
Where did the data come from?
● World Bank (public data portal)
How was the Data Visualisation put together?
● World Bank collates indicators from multiple sources
○ UNESCO, UNICEF, WHO, UNDESA, UNDP
● Author used freeware to create the viz
Why is it interesting?
● Targeted use of Global Data to highlight a specific cause / policy
● In this case, the effect of Primary Education on Income Levels
https://public.tableau.com/s/gallery/educating-girls
If you educate a Woman, you educate a Family

13. Viz #4 - Educating Girls
● For the year you were born, what country had the lowest rate of girls
finishing primary education?
● What was the average of this rate in High Income countries? What is
the year with the best completion rate?
● Where do you see the best improvement in the ratio of primary
education completion and reduced mortality?
For the eager ones!
● Which country has the highest ratio of completion to mortality over
any year?
https://public.tableau.com/s/gallery/educating-girls
Things to find...

14. Viz #5 - Right to Education
Where did the data come from?
● UNESCO Household Survey
How was the Data Visualisation put together?
● UNESCO developed an Interactive App to represent
the main issues in their Household Survey
Why is it interesting?
● Accessible style, no technical skill needed to understand message
● Clear Insights from the 126-page Regional Report
http://www.uis.unesco.org/_LAYOUTS/UNESCO/oosci-data-tool/index-en.html#en/KHM
Let’s EnRole Up Our Sleeves

15. Viz #5 - Right to Education
● What are the difference between children in India? Compare
○ Poorest vs Richest
○ In School vs Out of School
• What is the difference in school experience between Girls and Boys
in Pakistan?
• In Ethiopia what is the split between School vs Out of School
comparing rural and urban areas
For the eager ones!
• Of the Primary School Age Population in Nigeria, how many of the
poorest children are out of school?
http://www.uis.unesco.org/_LAYOUTS/UNESCO/oosci-data-tool/index-en.html#en/KHM
Things to find out ...

17. Hope you enjoyed our Workshop
DataDive
16/17 May 2015
Bank of Ireland,
Grand Canal Square
dublin@datakind.org
@DataKindDUB
#data4good
meetup.com/DataKind-DUB/

18. Thank you !
Join us: datakind.org/getinvolved