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Mobile Data Access for Public Good:

Cases and Caveats

Erik Wetter, PhD

Assistant Professor, Stockholm School of Economics

Chairman, Flowminder Foundation

Flowminder (Non-profit): Established to Work with Mobile Operators and International, Government Agencies

Sample mobile operator collaborations:

Sample donors and partners:

Dialogue partners on privacy and regulatory issues.

Academic affiliations and collaborations

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FLOWMINDER.ORG

Call Data Records (CDR) is billing information

(A) number – caller: anonymized

Cell_ID: location

TAC: Handset

Type: call, SMS, data, etc

Date & time

(B) number – receiving party: anonymized

Data volume

Mobile Network Data: Call Data Records (CDR)

Team Participated in Developing Dynamic Population

Mapping Using Mobile Data

Model built on phone usage and satellite data

The combination of phone network data and satellite-based

covariates produces accurate and dynamic population maps

that are relatively insensitive to network usage biases - Deville et al (2014) PNAS

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Team Pioneered Anonymized Mobile Network Data for Infectious Diseases: 2008- Zanzibar, Kenya Malaria

FLOWMINDER.ORG

Namibia work: Combined mobile and satellite data for improved intervention targeting (85% reduction of population at risk)

Reference: Tatem et al (2014) Malaria Journal

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Ouest

Sud

Centre

Artibonite

Nord-Est

Grande-Anse

Nord

Sud-Est

Nord-Ouest

Nippes

Average daily numbers of sims that moved out from the communal sections surroundingSaint-Marc, Oct 15 to Oct 23, 9:00 am, 2010.

Outbreak area

250

500

100

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Pioneered Anonymized Mobile Network Data for Crisis Response: 2010 Haiti Earthquake & Cholera Outbreak

Digicel HQ day after the earthquake

First Project (MDEEP) on CDR and Climate Migration: Bangladesh 2013

FLOWMINDER.ORG

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Nepal 2015 Earthquake: Data Access and Outputs in 14 days

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Flowminder Processing Flow

Operators Call Detail Records’ (CDRs)

including low-resolution location data

(nearest tower location) anonymized on

separate server hosted by operator.

Flowminder researchers conduct

analyses under operator

supervision, anonymous raw data

always behind operator firewall

Raw de-identified data does not leave mobile operator custody to avoid privacy, security & commercial concerns.

Non-sensitive aggregated

mobility estimates are exported,

Mobile operator firewall

Setup Fully Aligned with Mobile Industry (GSMA) Guidelines

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“A brilliant example of how the application of big data analysis to mobile

technologies can be used to accelerate emergency aid, and provide

intelligence to help prepare for future disasters.”

Mobile Industry Award 2016

Caveats and Limitations

FLOWMINDER.ORG

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The Star Trek Fallacy

1. Mobile data is a tool, not the solution – issue-driven vs. data-driven problem solving (data mining). • Expertise with the application topic is crucial.

2. Remote sensing data can augment but not replace field data (”ground truth”), eg. surveys.

3. Mobile network data is not a magic potion: • Mobile data is heterogenous – market/operators. • Representativeness – what does a SIM card represent? • Validity – value only when combined with other data.

4. Private sector data access • Privacy • Security concerns • Commercial concerns/conflicts of interest