BS ISO 19114 : 2003 AMD 15568

Foreword
Introduction
1 Scope
2 Conformance
3 Normative references
4 Terms and definitions
5 Abbreviated terms
6 Process for evaluating data quality
  6.1 General
  6.2 Components of the process
7 Data quality evaluation methods
  7.1 Classification of data quality evaluation methods
  7.2 Direct evaluation methods
  7.3 Indirect evaluation method
  7.4 Data quality evaluation examples
8 Reporting data quality evaluation information
  8.1 Reporting as metadata
  8.2 Reporting in a quality evaluation report
  8.3 Reporting aggregated data quality result
Annex A (normative) Abstract test suites
      A.1 Introduction
      A.2 Quality evaluation procedures
      A.3 Evaluating data quality
      A.4 Reporting data quality
Annex B (informative) Uses of quality evaluation procedures
      B.1 Introduction
      B.2 Development of a product specification or user
          requirements
      B.3 Quality control during dataset creation
      B.4 Inspection for conformance to a product specification
      B.5 Evaluation of dataset conformance to user requirements
      B.6 Quality control during dataset update
Annex C (informative) Applying quality evaluation procedures to
        dynamic datasets
      C.1 Introduction
      C.2 Determining and reporting the quality of a dynamic
          dataset
      C.3 Establishing continuous quality evaluation procedures
      C.4 Periodically re-establish the reference quality of the
          dataset
Annex D (informative) Examples of data quality measures
      D.1 Introduction
      D.2 Relationship of the data quality components
      D.3 Examples of data quality completeness measures
      D.4 Examples of data quality logical consistency measures
      D.5 Examples of data quality positional accuracy measures
      D.6 Examples of data quality temporal accuracy measures
      D.7 Examples of data quality thematic accuracy measures
Annex E (informative) Guidelines for sampling methods applied to
        geographic datasets
      E.1 Introduction
      E.2 Lot and item
      E.3 Sample size
      E.4 Sampling strategies
      E.5 Probability-based sampling
Annex F (informative) Example of testing for thematic accuracy
        and completeness
      F.1 Introduction
      F.2 Quality evaluation process
      F.3 Method for data quality evaluation
      F.4 Inspection for quality
      F.5 Determination of data quality results and conformance
      F.6 Reporting quality results
Annex G (informative) Example of measurement and reporting of
        completeness and thematic accuracy
      G.1 Introduction
      G.2 Dataset description
      G.3 Evaluation of data quality
      G.4 Reporting quality results
Annex H (informative) Example of an aggregated data quality
        result
      H.1 Introduction
      H.2 Dataset description
      H.3 Universe of discourse
      H.4 Dataset
      H.5 Aggregation of evaluation results and reporting
Annex I (normative) Reporting quality information in a quality
        evaluation report
      I.1 Introduction
      I.2 Quality evaluation report components
Annex J (informative) Aggregation of data quality results
      J.1 Introduction
      J.2 100 % pass/fail
      J.3 Weighted pass/fail
      J.4 Subset of results sufficient for product purpose
      J.5 Maximum/minimum value
Bibliography

Gives a framework of procedures for determining and evaluating quality that is applicable to digital geographic datasets, consistent with the data quality principles defined in ISO 19113. Applies to data producers when providing quality information on how well a dataset conforms to the product specification, and to data users attempting to determine whether or not the dataset contains data of sufficient quality to be fit for use in their particular applications.