From data to policy action in low income countries: how can innovation help?

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informing a data revolution right data, to the right people, at the right time, in the right format From data to policy action in low income countries: how can innovation help? Bangkok Regional Workshop July 17-18 ,2014

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From data to policy action in low income countries: how can innovation help?. Bangkok Regional Workshop. July 17-18 ,2014. a c all for a ction. - PowerPoint PPT Presentation

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Page 1: From data to policy action in low income countries: how can innovation help?

informing a data revolutionright data, to the right people, at the right time, in the right format

From data to policy action in low income countries: how can

innovation help?Bangkok Regional Workshop

July 17-18 ,2014

Page 2: From data to policy action in low income countries: how can innovation help?

a call for action“We should actively take advantage of new technology, crowd sourcing, and improved connectivity to empower people with information on the progress towards the targets.”

(From the UN Report of the High-Level Panel of Eminent Persons on the Post-2015 Development

Agenda)

Page 3: From data to policy action in low income countries: how can innovation help?

challenges• Difficult direct data collection due to the low penetration

of technology.• Difficult access to households.• Affordability of traditional methods of data collection.• Administrative data sources from the government not

available or not fit for the purpose.• Poor timeliness for example information becomes

available for analysis and policy action years after it has been collected.

• Lack of data at the dis-aggregated level that would be required to inform policy action.

• Information sharing and transparency is not widely adopted.

• Lack of skills and expertise to analyse and use data for policy action.

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innovation opportunitiesCase studies in the following areas:• Mobile Data Collection• New Data Sources• Crowd sourcing• Visualisation and GIS• Real-time collection and analysis• Open Data Dissemination

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Using mobile phones for data collection to support OVC in Tanzania

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Tracking Population Movements using Analysis of Mobile Phones Data in

Haiti

Source: irevolution.files.wordpress.com/2011/10/journal-pmed-mobile-phone-haiti.pdf

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Use of GIS-enabled Mobile Collection and Visualisation in Surui Carbon

Project

Source: rhiza.com/act/

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Demographic Explorer for Climate Adaptation (DECA) | Semarang,

Indonesia

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Real-time Data Monitoring

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New ways of disseminating knowledge

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Technological progress

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Open Data

Source: http://theodi.github.io/open-data-barometer-viz/

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Enablers• Standards and

frameworks• Technology• Methods• People• Partnerships• Funding

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Standards: International Aid Transparency Standard

Source: www.aidtransparency.net/

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Technology: Cloud-based Data Storage and Analysis

Source: International Journal of Computer Applications (0975 – 8887) Volume 74 – No.2, July 2013

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Methods: Advocacy Monitoring through Analysis of Big Social Data

Source: http://www.unglobalpulse.org/EWEC-social-data-analysis

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People: The Big Idea Pilot

Source: restlessdevelopment.org/big-idea-pilot

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Creating An Innovative Ecosystem: Network of Global Pulse Labs

Source: www.unglobalpulse.org/pulse-labs

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Funding: Rapid Impact and Vulnerability Analysis Fund (RIVAF)• Launched by the Global Pulse Initiative in December

2009 with funding from the UK’s Department for International Development (DfID) and the Government of Sweden.

• Supports innovative, real-time data collection and analysis to help develop a better understanding of how vulnerable populations cope with impacts of global crises.

• The RIVAF report includes summaries from eight research projects.

• Findings from the individual research projects revealed fascinating insights, painting a diverse picture of the impacts of global crises.

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Key Success Factors• Pilot project approach provides staged and controlled

environment to test how would innovation work in practice.

• Use of technology and methods, suitable for the environment in low-income countries, for example mobile infrastructure, GIS and visualisation.

• Leveraging alternative data sources by using crowd sourcing and harnessing new big data sources.

• Development, use and promotion of open data standards and practices to enable reuse of data and increase transparency.

• Partnerships across development organisations, government and private sectors that are crucial to mobilise skills and capabilities required for implementation.

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TRENDS ENABLERS INNOVATION AREAS

OUTCOMES

Cloud Technology Crowd sourcing Relevant

Mobile People Mobile Data collection

Timely

Social Methods Visualisation Accurate

Big Data Partnerships New Big Data sources

Coherent

Open Data Standards and frameworks

Open Data Dissemination

Accessible and Interpretable