Open Algorithms (OPAL) Project
OPAL (for Open Algorithms) is a collaborative project being developed by a group of partners committed to leveraging the power of platforms, big data and advanced analytics for the public good in a privacy-preserving, commercially sensible, stable, scalable, and sustainable manner.
OPAL’s core will consist of an open suite of softwares and open algorithms providing access to statistical information extracted from anonymized, secured and formatted data. These algorithms, accessed by an API, will be run on OPAL servers of partner companies, behind their firewalls. The vision is to strengthen the accuracy, timeliness and reliability of key development indicators and statistics of relevance for an array of users. The project will start with APIs to access indicators such as population density, mobility, approximations of poverty indices, or literacy rate based on mobile data from telecom operators as well as a library of certified open algorithms to extract these indicators in a governed and trustworthy manner.
The OPAL Project will also engage with data providers, users and analysts at all stages of its development, build local capacities and connections, and set-up local Data Governance and Advisory Boards for oversight and support of its operations.
Two pilots will be undertaken in the form of public-private-people partnerships in Senegal with Orange Sonatel and in Colombia with Telefónica. The aim during the pilot phase is to develop a Beta platform and a suite of open algorithms, all accessible as open source. These pilots will also assess the quality of the statistical indicators that are obtained from the platform. If the first two pilots are considered successful, the project could be extended to other developing countries.
Innovation: Big data, c’est données-donnant
Jeune Afrique, January 2018
OPAL: reconciling open innovation and data security
Uses and Value, November 2017
Fair, transparent and accountable algorithmic decision-making processes
Springer, 15 August 2017
The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good
Springer, 10 May 2017
Group Privacy: New Challenges of Data Technologies
Mettre le Big Data privé au service du bien public
Les Echos, 6 December 2016
Blockchain and Health IT: Algorithms, Privacy, and Data
White Paper for Office of the National Coordinator for Health Information Technology U.S. Department of Health and Human Services, 8 August 2016
Open Algorithms: a new paradigm for using private data for social good
Devex, 18 July 2016
DATa collaborative: OPAL
The Global Partnership for Sustainable Development Data
Climate and data: A critical combination for all our futures
TMForum, 11 April 2016
The ABCDE of Big Data: Assessing Biases in Call-detail records for Development Estimates
Revised Draft prepared for presentation at the Annual World Bank Conference on Development Economics 2016
OPAL: Privacy-conscientious use of mobile phone data
MIT Human Dynamics Lab