A data revolution for the MDGs / SDGs? What is big data The - PowerPoint PPT Presentation

A “data revolution” for the MDGs / SDGs?

• What is big data • The challenge • New partnerships for new data?

Th The MDG e MDGs da data a ga gap

An example in action

http://www.retale.com/info/retail-in-real-time/

“The future is already here, it is just not very evenly distributed”

http://www.premise.com/solutions.html

Quantified self: the new GDP?

4 ways to the data innovation 1. Funding and investment for national statistical capacity , particularly in developing countries. 2. Exploring new data sources, including those sourced from individual citizens. 3. Harnessing advanced technologies , like visualization tools that make data more understandable. 4. “ Liberating” data to “unleash the analytical creativity of users ” and hold policymakers accountable. U.N. Deputy Secretary-General Jan Eliasson

New data as a practice

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Types of data Example data sources Global Pulse works with: Soci cial al media ia data (blogs, ogs, forums, ums, soci cial al media ia • stream reams) s) Mobil bile e netwo work rk data (CDR DRs, s, top-up ups) s) • Radio dio feeds s • News ws media ia cont ntent ent • Online ne search arch • Post stal al data • GPS data • … • We gain access to this type of data through partnerships with private sector or academia.

TAKIN ING G THE POST-20 2015 15 PULS LSE http:/ ://pos /post2015. t2015.ungl unglobal obalpul pulse.net e.net

People express opinions 2500 Number of tweets per day Reports in Media which prompts spikes in tweets 2000 [2013/12/01] Debates about assurance of halal products. [2013/12/03] Uncertainty whether some drugs contain pig substance 1500 [2013/12/06] MoH starts consultations related to halal certification. [2013/12/07] Debates over halal certificates of food. [2013/12/12] Confirmation that some drugs and vaccines may contain 1000 haram substance. [2013/12/12] MUI urges pharmacologists to replace haram process. 500 0 2012-01-01 2012-02-01 2012-03-01 2012-04-01 2012-05-01 2012-06-01 2012-07-01 2012-08-01 2012-09-01 2012-10-01 2012-11-01 2012-12-01 2013-01-01 2013-02-01 2013-03-01 2013-04-01 2013-05-01 2013-06-01 2013-07-01 2013-08-01 2013-09-01 2013-10-01 2013-11-01 2013-12-01

Situational awareness “Is it dangerous to have fever, 3000 swelling, pain, “A baby suddenly died after vaccine?” “China is after vaccine ” 2000 investigating “There are some death cases autism cases after o f babies” 1000 MMR vaccine” 0 June 2012 Oct 2012 Apr 2013 Dec 2013 Rank 2012-06-20 2012-10-08 2013-04-28 2013-12-23 1 Autism (213) Death(1030) Fever (1498) Death (224) 2 Death (5) Fever (14) Swelling (1494) Fever (3) 3 Sick (4) Sick (4) Pain (1491) Crying (1) 4 Fever (2) Crying (3) Autism (1011) Autism (1) 5 Crying (1) Fever (3) Fever (4) -

Early warning and rapid response Early warning Rapid response with actionable plan Detect people concerned Disseminate correct information about death after vaccine through Twitter via influential users from Twitter @dr_piprim 1200 @dirgarambe 1000 @blogdoktor 800 …… 600 400 200 0 Number of tweets of ‘death’

Sinabung Eruption (15 th Sep, 2013) Infographics • Location : Karo regency, North Sumatra • Elevation : 2,460 m above sea level • Victims : BNPB (Indonesian National Board of Disaster Management) reported 15 people died, and more than 30,000 people Volume Dynamics from Twitter evacuated • Period: 14/9/2013 and 10/2/2014 • Total Twitter Posts: 151,448 • Relevant Posts: 117,436 (78%) • More than 10K tweets at the first eruption

Visualizing Displacement Due to Floods through Mobile Data Partners: WFP, Govt. of Mexico, Univ. of Madrid, Telefonica Project: Visual analytics to support improved targeting of humanitarian assistance during emergencies

CDRs population estimate vs census - state of Tabasco, Mexico Source: Telefonica

Luminosity as a proxy for GDP output Chen & Nordhaus, Using luminosity data as a proxy for economics statistics , 2011

A real-time map of poverty in Cote d’Ivoire? a) Abidjan b) Liberian border c) Roads to Mali and Burkina Faso d) Road to Ghana Ref: arxiv.org/abs/1309.4496: Evaluating Socio-Economic State Of A Country Analyzing Airtime Credit And Mobile Phone Datasets

Understanding labour market flows Source: Using social media to measure labour market flows, March 2014

Predicting Migration from Search Queries Partners: Google, UNFPA Project: Building a model that predicts intent to migrate based on Google search behavior.

Ev Evaluating luating policies icies real al ti time? e? A mobility index to evaluate H1N1 response in Mexico City Telefonica Research, 2011 (http://www.unglobalpulse.org/publicpolicyandcellphonedata)

New ew da data ta as as a a pr prac actic tice Those who Those who have done it talk about it Dev’t & Gov’t

Project portfolio Category Status Names 1. Social media for social protection 2. Social media to understand public perception of immunization Active 3. Signals of discrimination in the workplace 4. Nowcasting food prices and understanding coping mechanisms 5. Mapping socio economic vulnerability Research projects 6. Maternal health Exploration 7. Disaster response/resilience 8. Universal heath coverage/public service monitoring 9. Deforestation 10. Providing Real-Time Insights on Indonesian Post2015 Priorities Ad-hoc

Worki rking g with th us • Trainings/capacity building • Secondments & residencies • Advocacy and data hunting • Joint prototyping • Full research project

New data partnerships?

@gquaggiotto @pulselabjakarta

3 roles fo for NSOs Os and big data ta 1. 3 rd party to certify statistical quality of new sources 2. Issue statistical “best practices” in the use of non- traditional sources and the mining of “ big data ” 1. Use non-traditional sources to augment (and perhaps replace) official series Source: Andrew Wyckoff, OECD

Leveraging Partnerships to Enable Innovation Big Data Access Twitter (global, l, 500 million n message ges/da s/day) y) • Orange France Telecom (Ivory ry Coast, t, Senegal) l) • Telenor (Banglad adesh sh – mobile money data) • Telefonica (Mexico ico, , Guatemala emala) ) • XL (12 months s of CDRs from Indonesi esia) • MTN (Uganda) da) • Real Impact (Cote d’Ivoire, Rwanda, Zambia) • Universal Postal Union (global postal flow data) • Data Mining & Amazon Web Services (supercomputing) • DataSift (data filtering) • Analysis SAS (analytics & data visualization) • Technologies Crimson Hexagon (data analysis) • Data Science Université catholique de Louvain (call records • analysis) Expertise Institut des Systèmes Complexes de Paris Ile-de- • France (news media mining & filtering) Universidad Politécnica de Madrid (call records • analysis) Stockholm University (research fellow) • Karolinska Institutet (call records analysis) • University of Sheffield (speech-to-text tools) • Microsoft Research (social media analysis) •

GLOBAL PULSE: A NETWORK OF LABS Pulse Lab NYC Est. 2010 Pulse Lab Jakarta Est. 2012 Pulse Lab Kampala Est. 2013