Data quality

How well data meets the requirements of its intended use.

Quality can include accuracy, relevance, completeness, consistency and appropriate coverage. It is not a single universal property. A recording that fails one training requirement may still be valuable for another purpose, and a failed robot attempt can be useful data when it is accurately described.

In practice

A clear video is unsuitable for a particular task if its instruction and outcome labels do not match the recorded behavior.