Data quality allows users and user systems to assess fitness for use of the provided data. Data quality measures and the associated evaluation are reported as metadata of a data product. This metadata improves interoperability with other data products and provides usage by user groups that the data product was not originally intended for. The secondary users can make assessments of the data product usefulness in their application based on the reported data quality measures.
For this<Survey Metadata Product Specification> the following Data Quality Elements will be assessed[1]:
Conformance to this Product Specification
Intended purpose of the data product
Completeness of the data product in terms of coverage
Logical Consistency
Positional Uncertainty and Accuracy
Thematic Accuracy
Temporal Quality
Aggregation measures
Validation checks or conformance checks including:
General tests for dataset integrity;
Specific tests for a specific data model.
Attribution within the metadata record
Quality references in the Abstract and/or Lineage, although the ISO19115 Data quality elements within (MD_DataQuality) can also be used to document precision and accuracy more fully.
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[1] As deemed necessary by the IHO –Hydrographic Standards and Services Committee