The Global Partnership for Sustainable Development Data and the World Bank’s Development Data Group announce the ten recipients of the Collaborative Data Innovations for Sustainable Development Pilot Funding.

In July of 2016, the Global Partnership for Sustainable Development Data, announced a new multi-million dollar funding initiative to support collaborative data innovations for sustainable development.  Today, the Partnership, working in close collaboration with the World Bank’s Development Data Group, is delighted to announce the recipients of the pilot round of this initiative.

As part of the Collaborative Data Innovations for Sustainable Development Pilot Funding, which is supported by the World Bank’s Trust Fund for Statistical Capacity Building (TFSCB), the Global Partnership will support 10 projects in data production, dissemination and use, primarily in low­-income and lower­-middle-­income countries.

From improving vital registration of Syrian refugees in Lebanon to helping health workers predict patient behavior in Africa, from using low-orbit satellites to detect illegal fishing in Southeast Asia to using signal attenuation between mobile phone towers to estimate rainfall, the selected projects include a rich mix of innovations in development data being carried out in 20 countries across Africa, the Middle East, and Asia. 

While these projects cover a variety of sectors and SDGs, their unifying goal is to encourage collaboration, experimentation, learning, and capacity development in the field of sustainable development data, especially where needs are continuous or recurrent, and where innovations can be readily adapted to other regions and sectors.

What´s particularly exciting about the funding provided by the Global Partnership for Sustainable Development Data is that it is focused on solving real problems facing real people in the world. -- Nathaniel Heller, Managing Director, Results for Development Institute [Innovation Fund Recipient]

We are committed to learning from the projects’ successes and failures as they are implemented over the next 18 months. This is vital for any innovation work. The results and lessons learned from these projects will be openly available to all, and will help to shape the themes and priority for future rounds of funding. The process has been a joint effort between the World Bank and the Global Partnership. Innovation financing was one of the World Bank’s commitments when it joined the Global Partnership, and the Partnership provided a network of ideas, individuals and institutions that resulted in the submission of over 400 proposals for this pilot round of financing.


Activity 1

  • Project Title: Smart Water Monitoring and Alert with Rainfall Measurement from Telecommunications Networks 
  • Lead Organization: Institut de Recherche pour le Développement
  • Collaborating Organizations: Mobile operators (Meditel in Morocco and Orange in Cameroon), local universities in three African countries, and two startups (GEOVECTORIX and Africasys)
  • Location: Cameroon and Morocco
  • Description: The main objective of the “Flood Alert and Water Monitoring System” project is to test operationalization of a mobile-data driven system for monitoring rainfall and issuing real-time alerts in an urban African context. This innovative, cost-effective system will address data gaps in quality climate, rainfall and water data and help local and sub-regional authorities improve urban flood and water management on a sustainable basis. Secondary objectives are to capture feedback on the system and build awareness and capacity for a wider scaling of this new technique.

Activity 2

  • Project Title: Wetlands Monitoring with Earth Observation Data
  • Lead Organization: Ramsar Center for Eastern Africa
  • Collaborating Organizations: DHI GRAS, the University of Twente and the European Space Agency
  • Location: Uganda
  • Description: The objective of this activity is to explore the potential of earth observation (EO) satellite data for taking stock of and monitoring wetlands, a vital component of the global water resources ecosystem. This activity will pilot design and development of a user friendly digital system for use by the Ugandan Ministry of Water and Environment, to enable national authorities to generate spatial time series statistical data for taking inventory and monitoring national wetland resources train the government on its use and produce a roadmap for scaling to other countries of East Africa. This is a unique attempt to demonstrate the potential of satellite-derived EO data to provide a full national wetland inventory in Uganda, which has been a pilot country for monitoring of SDG Target 6.6.

Activity 3 

  • Project Title: Use of Big Data and Weak-Signal Analysis to Counter Human Trafficking and Illegal, Unreported, Unregulated (IUU) Fishing
  • Lead Organization: Novametrics
  • Collaborating Organizations: Pew Charitable Trusts, Social Impact and International Justice Mission
  • Location: Southeast Asia, East Africa
  • Description: Human trafficking and IUU fishing are ubiquitous within the commercial seafood industry in low and lower-middle income economies that participate in commercial fishing or send migrants to countries that do. While there is little direct data on human trafficking and IUU fishing, there is a large amount of indirect data that can be used to characterize the ecosystem in which these activities occur. The project’s objectives are to use big-data analytics and weak-signal analysis to help locate high risk “hotspots”, provide evidence to support political action and prosecution, and to identify the most cost-effective interventions for both current and future high-risk areas.

Activity 4 

  • Project Title: Predictive Analytics to Assess Defaulter Risk at Point of Care
  • Lead Organization: Dimagi
  • Collaborating Organizations: mothers2mothers, Small Project Foundation,DataProphet Pty. Ltd., and the Department of Computer Science of the University of Cape Town
  • Location: 2 countries in Africa
  • Description: The objective of this project is to use predictive machine learning technology to help front line health workers in Africa to identify, at the point of care, patients who are likely to fail to return for HIV (and other diseases, such as TB) treatment. By quantifying the underlying risk factors of LTFU, and building data-driven decision making into a low-cost information system for care providers this activity will equip the health workers with a decision-assisting job aid to help them take action on patients at high risk of not returning, and thus cut down on costs related to trying to locate and contact non-returning patients.

Activity 5

  • Project Title: Advancing Civil Registration and Vital Statistics (CRVS) Systems in the Service of Syrian Refugees
  • Lead Organization: UNESCWA
  • Collaborating Organizations: World Health Organization, UNICEF, and FAFO (a Norwegian research foundation), with additional technical and academic support provided by the Catholic University of Louvain (Belgium)
  • Location: Lebanon, Jordan
  • Description: There is currently a lack of knowledge of the level of completeness of vital registration for Syrian refugees, nor have there been any formal assessments of the data quality of these administrative data systems in countries neighboring active conflict zones. The objectives of this project are three-fold – (1) to evaluate the vital registration systems for Syrian refugees in Lebanon and Jordan, (2) to enhance knowledge sharing and to support coordination of efforts amongst those seeking to improve the responsiveness of CRVS systems to the refugees’ needs in Lebanon and Jordan, and (3)  to enhance the capacity of Lebanon and Jordan with regards to these systems.

Activity 6 

  • Project Title: Leveraging Informal Waste Ecosystem for Better Management of Post-consumer Recyclable Waste in Urban India
  • Lead Organization: Kabadiwalla Connect
  • Collaborating Organizations: India Institute of Science, Infosystems, and South India AIDS Action Programme
  • Location: India
  • Description: The objective of this project is to contribute to the achievement of SDGs by providing a framework that cities in low and middle income countries around the world can use to manage their waste more efficiently by collaborating with the informal recycling sector. The team will conduct a census by surveying and mapping stakeholders in the informal waste ecosystem in Chennai, India, which will be the first attempt to collect such data. It will then conduct experiments to explore incentives, policy mechanisms and technology that can nudge communities to more sustainable practices for waste generation and management, while also exploring ways to integrate it into the more formal waste management strategies employed by the local municipality.

Activity 7

  • Project Title: Building a Data Collaborative to support SDGs on Health and WASH
  • Lead Organization: Netherlands Red Cross
  • Collaborating Organizations: CartONG and Malawi Red Cross Society
  • Location: Malawi, the Democratic Republic of the Congo
  • Description: This project aims to strengthen data collaboration between development and humanitarian actors, Volunteer Technical Communities (VTCs), as well as governments and academia to be able to make more effective decisions on Health and Water, Sanitation and Hygiene (WASH) interventions, and to support the monitoring and reporting of the SDGs. It will create proof-of-concept Data Collaboratives in two countries, and evaluate their impact.  It will also test the use of non-official crowdsourced data as proxies for SDGs monitoring.

Activity 8 

  • Project Title: Catalyzing Data-driven Market-based Solutions to Small Holder Farmer Fertilizer Uptake
  • Lead Organization: Results for Development Institute
  • Collaborating Organizations: Local Development Research Institute
  • Location: Kenya
  • Description: Unfortunately, data on fertilizer usage and supply is notoriously poor in a majority of low-income countries. Poor data and information gaps frequently are a root cause of market breakdowns, resulting in dysfunctional fertilizer distribution systems which in turn depress food production.  The project objectives are to fill the data gaps and to develop and test new approaches to incentivizing the collection and use of key fertilizer data. The team hypothesizes that availability of quality data combined with increased capacity of the public and private sector stakeholders to use this data will accelerate market-based solutions to delivering higher-quality fertilizer to small holder rural farmers at the right moment in the planting season.

Activity 9

  • Project Title: Mapping Night Time Fishing Activity
  • Lead Organization: University of Colorado Boulder
  • Collaborating Organizations: National Oceanic and Atmospheric Administration
  • Location: Southeast Asia
  • Description: The objective of the “Mapping Night Time Fishing Activity” project is to collect and make available boat detection data to government agencies, the scientific community and environmental groups. This previously unavailable data will characterize long term nighttime fishing activity in Southeast Asia.  The team will apply a new method of data collection based on the use of enhanced sensors on low-orbit satellites to detect the kind of lights used by fishermen to attract fish.

Activity 10

  • Project Title: Dynamic Census
  • Lead Organization: University of Tokyo
  • Collaborating Organizations: LIRNEasia
  • Location: Sri Lanka
  • Description:  The conventional approach to understanding national populations is through the decennial National Housing and Population Census, which provides a variety of indicators. However, census data often tend to be outdated in resource scarce countries due to the enormous time and monetary cost required for data gathering. This activity aims to improve the existing census approach by deriving insights from call detail records (CDR). It will supplement population and housing census data by adding dynamic aspects of population distribution to changes in population distribution over time, at high frequency.