Data Entry Workflows#
According to Library Carpentry’s Tidy Data for Librarians tutorial, “Quality assurance stops bad data from ever being entered by checking to see if values are valid during data entry. For example, if research is being conducted at sites A, B, and C, then the value V (which is right next to B on the keyboard) should never be entered. Likewise if one of the kinds of data being collected is a count, only integers greater than or equal to zero should be allowed.”
Building in quality assurance constraints into a data entry workflow can help minimize pattern errors that require later cleaning.