Explains the ISO/IEC 25012 data quality characteristics
Inherent characteristics (accuracy, completeness, consistency, credibility, currentness) and system-dependent ones. Accuracy is syntactic (the value is a valid value of its domain) or semantic (the value is the true one, which needs a reference such as a schedule or the ledger) (ISO/IEC 25012:2008).
Can AI do this?
AI does this well Most of the tested AI models master this. 3 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 100% | Not shown |
| gpt-6-luna | Low cost | 100% | Mastered |
| claude-haiku-5-5 | Low cost | 100% | Mastered |
Mastered means a probability of at least 90% that the model has this knobit, estimated from its graded answers. “Not shown” means the answers do not settle it either way. How the models are tested.
What it looks like in practice
Expected result: Inherent characteristics (accuracy, completeness, consistency, credibility, currentness) and system-dependent ones. Accuracy is syntactic (the value is a valid value of its domain) or semantic (the value is the true one, which needs a reference such as a schedule or the ledger) (ISO/IEC 25012:2008).
How it is assessed: Answers a written question on the ISO/IEC 25012 data quality characteristic correctly
Related knobits
Builds on
Needed for
- Q-403 Recognises a quality measurement labelled with a characteristic it does not test
- Q-453 Explains ISO/IEC 25024 data quality measures
- Q-705 Recognises a service level measure unable to detect the element's failure
All 10 knobits of Profile and assess data quality.
Source: Practice the stage 4 reference and review checklist rest on