High quality data is often understood as valid, accurate, complete, consistent, and uniformed. This is often achieved through the cleaning process.
Measurements are valid when they conform to set constraints. They are accurate when they represent the correct values (often requiring cross-referencing trusted external sources). They are complete when they represent everything that might be known and are consistent when observations do not contradict each other. Measurements are uniform when the same unit of measure is used in all relevant measurements.