Govern and Evaluate Research Data Quality

Overview

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This course builds data governance and quality management capabilities for research professionals. Learners will develop skills in applying metadata tagging for effective data governance and evaluating data quality against defined standards. Through practical application, learners will build the technical capabilities needed to implement robust data management practices that ensure information integrity and accessibility.

Syllabus

Metadata Tagging and Asset Governance

This module introduces the core principles of data governance and the critical role of metadata. Learners will explore why consistent data tagging is essential for preventing costly errors, using real-world examples as a guide. They will learn how to interpret governance policies to determine and apply correct metadata, transforming raw data into reliable, governed assets.

Data Quality Monitoring and Remediation

In this module, learners shift from establishing governance to maintaining it. They will learn how to monitor data quality by evaluating Key Performance Indicators (KPIs) against organizational standards. Using a case study based on the UK Government's COVID-19 data error, learners will practice identifying quality failures and creating formal issue tickets to drive the remediation process, ensuring data remains trustworthy over time.