Week 1: Module I — Advancing development objectives through data
Introduction to harnessing the value of data for better lives for the poor through the three pathways set out in a conceptual framework, economics and politics of data, and overview of a data governance framework to realize the development impact.
Week 2: Module II — Data in the public sector, the private sector, and civil society
Illustration of how data can be used as a force for public good, as a resource for the private sector, and to inform civil society and empower individuals, using several real-life examples.
Week 3: Module III — Creative reuses of data for greater value
Overview of how innovations in repurposing and combining public intent and private intent data are opening doors to development impacts previously unimaginable. Introduction to the potential and limitations of reuse, interoperability, and synergies of public intent and private intent data.
Week 4: Module IV — Aligning data governance with the new social contract
Introduction to critical data infrastructure policies to ensure equitable access for poor people in poor countries; and introduction to data policies, laws and regulations, using a safeguards and enablers framework, to create a trust environment to meet the needs of the rapidly evolving data economy.
Week 5: Module V — Creating value in the data economy: The role of competition, trade, and tax policy
Overview of how the expanding role of data in ubiquitous platform business models is reshaping competition, trade, and taxation in the real economy and posing pertinent risks for low- and middle-income countries. Introduction to the policy challenges and responses arising from competition, trade and taxation, and the linkages with the design of data regulations.
Week 6: Module VI — Moving toward an integrated national data system
Introduction to understanding how institutional ecosystems can help govern data through collective action, and furthermore, the steps for creating an aspirational integrated national data system, using a maturity model approach, and the tools for measuring performance of data systems.