Developing automated data cleansing and validation processes for fisheries catch and effort data

The industry has identified the need for automated data cleansing and diagnostic procedures that can be applied to large fisheries databases to detect and identify errors and provide subsets of reliable catch and effort data for stock assessments and other analyses. This project will develop automated processes to routinely assess newly entered fisheries catch, retrospectively quantify error rates in existing data and assess their likely influence on the outputs of stock assessment analyses.