The fundamentals of quality assurance never change. Completeness, validity, logical consistency, physical consistency, referential integrity, and positional accuracy are the cornerstones of the QA plan. All well-designed QA strategies must coexist within the processes that create and maintain the data and must incorporate key elements from the classic QA categories. If QA is not integrated within the GIS project, QA procedures can themselves become sources of error. All data must conform to a known standard for topology, table structure, precision, projection, and other data model specific requirements.
Validity measures the attribute accuracy of the database.
Each attribute must have a defined domain and range. The domain is the set of all legal values for the attribute. The range is the set of values within which the data must fall. If the value of one attribute changes, the values of functionally related attributes must also change. For example, the requirement that all electrical transformers in an electrical distribution database's GIS have annotation denoting phasing placed within 15 feet of the transformer object is one that describes a physically consistent spatial requirement.