Data Quality Contextual Relationships Framework
Overview
Data quality can be assessed through four distinct contextual relationships, each revealing different quality dimensions:
| Relationship | Quality Focus | Example Dimensions |
|---|---|---|
| Intrinsic | Data itself | Accuracy, consistency, completeness |
| User | Data ↔ consumers | Understandability, relevance, credibility |
| System | Data ↔ infrastructure | Availability, security, timeliness |
| Society | Data ↔ community | Bias-freedom, provenance, diversity |
Why This Matters
Quality assessments that focus only on intrinsic properties miss crucial contextual factors. A dataset can be accurate and consistent but still fail users (incomprehensible), systems (unavailable when needed), or society (perpetuating bias).
The “fitness for use” principle requires evaluating all relevant relationships, but which relationships matter depends on the use case.
How to Apply
When defining or assessing data quality:
- Identify stakeholders: Who are the data users? What systems process the data? What broader community is affected?
- Map relationships: For each quality dimension you care about, determine which contextual relationship it belongs to
- Prioritize by context: A real-time analytics system emphasizes system relationships (availability, timeliness); a public dataset emphasizes societal relationships (bias, provenance)
- Assess comprehensively: Check that your quality framework covers all relevant relationships
When This Especially Matters
- Data integration from multiple sources (system relationships dominate)
- User-facing analytics tools (user relationships dominate)
- AI training data (societal relationships critical)
- Regulatory compliance contexts (may require all four)
Limitations
The boundaries between categories aren’t always clean, completeness can be intrinsic or contextual depending on how you define it. The framework is a lens for thinking, not a rigid classification.
Related: 04-atom—intrinsic-vs-contextual-quality, 04-atom—fitness-for-use-definition, 04-atom—five-core-dq-dimensions