Dimensions of Data Quality
Table 1
Table
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Table 1
Table
Table 1
| Dimension | Meaning | Example quality check |
|---|---|---|
| Accuracy | Values reflect source documents or true observations | Compare database value with laboratory report |
| Completeness | Expected data are present or missingness is explained | List participants missing primary outcome |
| Validity | Values conform to allowed formats, ranges, and codes | Temperature must be 30-45 degrees Celsius |
| Consistency | Related values agree logically | Follow-up date must occur after enrollment date |
| Timeliness | Data are available within expected timeframes | Forms entered within 72 hours of visit |
| Uniqueness | Records are not unintentionally duplicated | Identify duplicate participant IDs |
| Integrity | Data are protected from unauthorized change | Review audit trail for critical edits |
| Interpretability | Data can be understood by users and analysts | Verify data dictionary and coding definitions |