Once the data collection system has been set up vigilance is required to ensure that the information that is being recorded and submitted is true, accurate and that it arrives on timely basis so its essential value is retained. Data errors are inevitable; the challenge is in having a system that will find and correct these errors and to produce data with recognised integrity.

A comprehensive data quality system will include: 

• Training for data recorders
• Methods and training for identifying errors on the hard copy; at the point of submission and during data entry.
• Data quality control in databases (i.e. cross-checks, range checks, data reconciliation and double-entry).
• A feedback mechanism, so that errors found in one part of the tuna data system will be corrected at the source and the relevant people properly informed.

• Documented procedures which show the action to take with the data as they flow through the system. Documented procedures ensure staff are aware of what action to take, what their own role is and provides them with the overall picture for tuna data. Written procedures also offer a template for any structured review.
• Scheduled revisions of the tuna data systems which ensures input from relevant staff and other stakeholders.