THE DIMENSIONS OF DATA QUALITY
There are two main dimensions of data quality – completeness and correctness. Completeness assesses the extent to which the data reflects the real-world situation. Correctness, on the other hand, assesses whether the data complies with the appropriate constraints and validation rules and whether it accurately reflects the real-world situation. These two dimensions of data quality apply to both metadata and occurrence data, as shown in Figure 7.1.
When considering the quality of metadata, all the data models, all the names for the data ‘objects’ and all of the physical implementations (specified using data definition languages (DDL) such as the data definition capabilities included in SQL) must be assessed in terms ...
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