Open Government Data Program Management Training Course

Course Overview

Learning Objectives

• Explain open government data principles and their role in transparency, innovation, and public value.
• Interpret national open data policies, mandates, and licensing models applicable to government entities.
• Design an open data program governance model with clear roles, responsibilities, and approval workflows.
• Build and maintain a government data inventory as the foundation for publication decisions.
• Prioritize datasets for release using demand, public value, readiness, and risk criteria.
• Apply open format, metadata, and machine-readability standards to published government datasets.
• Evaluate portal, API, and bulk-download options for publishing and maintaining government data.
• Apply structured data quality checks before and after the publication of open datasets.
• Apply anonymization and statistical disclosure control techniques to reduce re-identification risk.
• Develop user engagement and reuse activities with businesses, researchers, media, and civil society.
• Assess open data program performance against the criteria of international open data indices.
• Develop a practical roadmap for launching or strengthening a government open data program.

Who Should Attend

Learning Outcomes

• Explain the principles, value, and policy foundations of open government data.
• Interpret national open data policies and select appropriate open licenses and reuse terms.
• Design a governance model for an open data program with defined roles and approval workflows.
• Build a government data inventory and classify datasets for open, shared, or restricted access.
• Prioritize datasets for publication using structured value, demand, readiness, and risk criteria.
• Prepare datasets in open, machine-readable formats with complete and consistent metadata.
• Evaluate open data portal functions, APIs, and publication channels against user needs.
• Apply pre-publication data quality checks and manage corrections to published data.
• Identify direct and indirect identifiers and assess re-identification risk in government datasets.
• Apply anonymization and statistical disclosure control techniques before releasing data.
• Design user engagement activities that increase the reuse and public value of open data.
• Measure program performance and prepare evidence for international open data assessments.
• Develop a practical roadmap for launching or strengthening a government open data program.

Course Outline