Accounting for Data Gaps and Uncertainty in Pipeline Risk Assessment and Integrity Assurance

This white paper examines the growing role of data quality in modern pipeline riskA measure of loss in terms of both the incident likelihood of occurrence and the magnitude of the consequences. modelling and probabilistic risk assessments (PRA). It introduces a Data Quality Management Framework designed to help operators evaluate uncertainty, improve risk model accuracy, support regulatory compliance, and optimize data-driven decision-making.