The data quality concept has a number of constituents depending on the context – also named Data Quality Dimensions. For Met-Ocean observations a commonly used classification is:
• Instrumentation checks and calibration
• Documentation of deployment attributes, parameters, sampling schemes etc.
• Quality Control Scheme applied to the dataset – automatic, semi-automatic, and eventually manual
• Met-Ocean assessment of the reasonableness of the data
Conceptual research on the data quality issue the last decade has resulted in more generic and complete quality dimension specification. The data quality dimensions used at DQS is provided by Danette McGilvray in the book “Executing Data Quality Projects – Ten Steps to Quality Data and Trusted Information”, 2008:
1. Data Specification
2. Data Integrity Fundamentals
3. Duplication
4. Accuracy
5. Consistency and Synchronization
6. Timeliness and Availability
7. Ease of Use and Maintainability
8. Data Coverage
9. Presentation Quality
10. Perception, Relevance, and Trust
11. Data Decay
12. Transactability
