TA 2. Innovations and synergies across different data ecosystems

(TA2.22) The Open Algorithms (OPAL) Project: What has been achieved in Senegal and Colombia and how can it scale?


Ajman Stat Hall October 24, 2018 10:45 am - 12:00 pm

Bookmark and Share

Sandra Moreno
Nicolas de Cordes
William Hoffman
Claire Melamed
Pedro de Alarcon
Seydina Ousmane Sene
Emmanuel Letouzé
Natalie Grover


This interactive workshop will have 2 main objectives structuring its agenda:

  1. Present and discuss the key results and lessons of the Open Algorithms (OPAL) pilots in Senegal and Colombia, developed since 2016 with core funding from the French Development Agency (AFD) in partnership with 2 leading telecom operators Orange-Sonatel and Telefónica, and their National Statistical Offices;
  2. Discuss and get inputs on needs and requirements for scaling OPAL to other countries and industries to allow policymakers and official statisticians in particular to utilize private data sources as part of their day to day jobs in a safe ethical manner.

OPAL is a techno-institutional innovation developed by a consortium composed of Data-Pop Alliance, Imperial College London, the MIT Media Lab, Orange and the World Economic Forum, as a key milestone towards a vision where data is at the heart of sustainable societal development around the globe. It came out of the recognition that using ‘big data ' sources held by private companies for research and policy purposes in a safe and systemic way has been a conundrum, for legitimate commercial and ethical reasons.

In that context, OPAL 's 2 main goals are to provide a better picture of human reality to official statisticians, policy makers, planners, businesses, and citizens in a safe, scalable, socially and economically sustainable manner by "sending the code (open algorithms) to the data", while enabling greater inclusion and inputs of all members of societies on the kinds and uses of analyses performed on data about themselves.

To that end, OPAL is built around two major components: a technological component with an open-source secured platform and suite of algorithms extracting key development indicators (such as population densities) from private sector data (e.g. telecom data in the current pilots) and (ii) a governance component, with a participatory design, an ethics committee, and capacity building activities.

The workshop will showcase the best use cases in both pilot countries, offer an opportunity for participants to experiment with the platform, allow an open discussion on the key outcomes, successes and challenges of the pilots, and explore options and requirements for expanding OPAL to other geographies and industries in 2019 and beyond to foster evidence-based decision making through the ethical use of big data sources at scale.