OPAL Project

OPAL (for "Open Algorithms") is a philosophy and an ecosystem that aims to bring hard data to hard problems. It started as an socio-technological innovation developed by a group of partners around MIT Media Lab, Imperial College London, Orange, World Economic Forum and Data-Pop Alliance. As of 2023, the initiative is run by Data-Pop Alliance. Through its question-and-answer approach, OPAL aims to unlock the potential of sensitive data for public good purposes in a safe, scalable, inclusive, and socially and economically sustainable manner, in full compliance with GDPR and all relevant regulations and ethical guidelines and frameworks. OPAL’s core is a privacy-preserving architecture supported by a participatory governance mechanism that allow getting answers to complex questions in the form of statistical indicators and insights. These are obtained by querying sensitive data without these data ever being shared and exposed by « sending the code to the data » through open algorithms rather than the other way around. By combining the collective richness of « hard-to-reach data » such as mobile phone metadata, financial transactions, earth observation data, administrative records, microdata from statistical offices, but also survey data collected in complex settings on complex questions, it is designed to provide a better picture of human reality to official statisticians, policymakers, businesses, investors and citizens, while fostering inclusion and inputs of all on the kinds and uses of analysis performed on data about individuals and communities represented in these datasets. Its use cases and application domains include analyses of climate change effects, education, health and transportation, poverty and vulnerability, monitoring and evaluation of public policies and programs, private investment decisions and impact assessments, among others. The ultimate value proposition of OPAL is to provide hard data to tackle hard problems.