Data editing is the control, scrutiny, and correction of data. It is also called data cleaning. The principles for data editing are general and intended to be applicable for all statistical production.
Nine principles for data editing in SSB are proposed, providing general guidelines for when and how data editing should be done. Editing in SSB should be automated as much as possible, but human control and intervention in the processes must be possible.
The guidelines are a specification of the principles. They are intended to be suitable for as many statistics as possible, hence the differentiation between social and business statistics in some processes. The guidelines are designed to serve as a handbook of good practice in editing work, specifying what should be controlled and how. Additionally, the guidelines include the recommended quality indicators for different parts of the editing process.