1. Data Validation Methods WFD GIS Working Group
Albrecht Wirthmann
Eurostat - unit E4 / GISCO
BECH D3/720
+(352)

2. Data Validation methods
ISO quality principles
ISO quality evaluation procedures
GISCO quality assessment and control
ISO Meatadata for quality description

3. Usage of ISO standard Evaluate quality of a dataset
Identify and report quality information
Specify application schema
Develop product specifications and user requirements

4. Data quality concepts Real World Data producer Data user
Universe of discourse B
Universe of discourse
Data producer
Data user
Data quality
Data quality
User requirements
Product specification
Dataset

5. Quality Description Metadata in file or repository
Dataset series
Metadata in file or repository
Dataset
Smaller groupings of data
features, f. attributes, f. relationships,
common characteristics
Attribute in dataset
Feature instance, attribute, relationship

6. Quality description
Data quality overview elements General, non-quantitative information
Data quality elements How well are product specifications met

7. Data quality elements Completeness Logical consistency
Positional accuracy
Temporal accuracy
Thematic accuracy

8. Data quality subelements
Completeness
Commission excess data present in a dataset
Omission data absent from a dataset

9. Data quality subelements
Logical consistency
Conceptual consistency Adherence to rules of conceptual schema
Domain consistency Adherence of values to value domains
Topological consistency Correctness of explicitly encoded topological characteristics

10. Data quality subelements
Positional Accuracy
Absolute accuracy Comparison with “true” values
Relative accuracy Comparison of positions between features
Gridded data position accuracy Comparison of position of grid element with its “true” position

11. Data quality subelements
Temporal accuracy
Accuracy of a time measurement
Temporal consistency Correctness of ordered events
Temporal validity Validity of data with respect to time

12. Data quality subelements
Thematic accuracy
classification correctness Comparison of classification to universe of discourse
non-quantitative attribute correctness Correctness of non-quantitative attributes
quantitative attribute correctness Accuracy of quantitative attributes

13. Descriptors of data quality subelements
Scope
Measure
Evaluation procedure
Result
Value type
Value unit
Date

14. When to report quality information
Data is deleted, added or modified
Product specifications change
Real world changes, time aspect

15. Process for evaluating data quality
Product specification available
Define dataset
Identify applicable data quality element, subelement and data quality scope
Identify data quality measure
Select and apply data quality evaluation method
Determine data quality result
Determine conformance
Report data quality result

16. Data quality evaluation methods
Direct evaluation method
Indirect evaluation method
Internal
External

17. Examples for validation
Existence and validity of attribute values
Connectivity of surface water network
Coordinates located in country, water basin
Do water basins fit between countries
Validity of domains
Validity of classification

18. Open questions Which data will be transferred?
What will be the data model?
Who applies data validation?
Member states
European Commission
Should reported data quality be validated?
Which layers are validated?
Are layers validated differently?