Measurement and Development
Data-Pop Alliance has ongoing research and programs around measurement and Sustainable Development. Our work in this field aims to contribute to the international community’s debate on the role of innovative methodologies, including new approaches based on artificial intelligence and Big Data, in ensuring global accountability towards the UN Agenda 2030 for Sustainable Development. Our research is presented in papers, focused discussions and workshops.
Research and Implementation
Measuring the Unmeasured: Tier 3 SDGs
Developed in partnership with UNDP, this project seeks to enable governments to identify, collect and use non-classic sources of data to measure SDG Tier III indicators (for which ‘No internationally established methodology or standards are yet available for the indicator, but methodology/standards are being, or will be, developed or tested.’) at a national level and apply the results in policy-making in priority areas.
Human mobility and population density in the Maldives
Together with UNFPA and the National Bureau of Statistics Data-Pop alliance launched a project in the Maldives, a nation of half million people dispersed over more than 1,000 islands, where the last demographic count took place in 2014. The migration rate, both of foreign workers and people moving towards the greater Male’ area, is expected to increase in the coming decades. The main goal of this pilot is to explore new methodologies to produce high quality statistics of these trends in the capital city of Male’, with the possibility to scale to the rest of the country.
Measuring Development Effectiveness
How has the Monitoring and Evaluation (M&E) of development projects changed in the last decades? Do we see new trends for the coming years? In the age of ‘goals’ and ‘targets’ is there a true agreement on the definition of development effectiveness? Can we leverage Big Data and AI to ensure a shift from “proving” to “improving”? These are some of the questions tackled in our research on how to best measure the impact of development interventions and programs.
Harnessing Big Data and Artificial Intelligence for Development Effectiveness
Emmanuel Letouzé, Micol Stock
Forthcoming: "Does Data Matter for Development? A Preliminary Look at the Evidence"
Emmanuel Letouzé, Julie Ricard, Micol Stock,
and Rodrigo Lara Molina
"Big Data and Development: an Overview"
Emmanuel Letouzé, in collaboration with SciDev.net and the World Bank Group