Cross-Framework Mapping

ISO/IEC 25012:2008 - Data Quality ModelvsJapan AI Guidelines

See exactly how ISO/IEC 25012:2008 - Data Quality Model controls map to Japan AI Guidelines. Pre-computed mappings, identified gaps, and coverage analysis.

4
Controls Mapped
32
Gaps Found
11%
Coverage

According to the TheArtOfService Compliance Knowledge Graph:

ISO/IEC 25012:2008 - Data Quality Model maps to Japan AI Guidelines with 11% coverage across 4 directly mapped controls. Analysis of 36 ISO/IEC 25012:2008 - Data Quality Model controls identifies 32 compliance gaps — primarily concentrated in Inherent and System-Dependent.

Source: TheArtOfService Knowledge Graph | 36 controls analysed | 718 frameworks | 330K+ cross-framework mappings

Control Mappings

Showing 4 of 4 mapped controls across 2 domains. Sign up to explore all 330K+ mappings across 718 frameworks.

System-Dependent Data Quality Characteristics(1 mappings)

ISO-25012-4.13Availability
JP-AIG-Safety-Validation-Testing-Robustness-AISI-AI-Safety-Institute-Pre-Deployment-Evaluation-Red-TeamingJapan AI Guidelines Safety + Validation + Testing + Robustness + AISI AI Safety Institute (14 Feb 2024) + Pre-Deployment Evaluation + Red Teaming + Capability Evaluations + AI Incident Database + Safe Deployment + AI Safety Reports

Data Quality Model Application(3 mappings)

ISO-25012-5.1Establishing data quality requirements
JP-AIG-Data-Governance-Training-Data-Quality-Provenance-Lineage-Copyright-APPI-Personal-Information-ProtectionJapan AI Guidelines Data Governance + Training Data Quality + Provenance + Lineage + Copyright Act 2018 Article 30-4 Text Data Mining Exception + APPI 2022 Amendment + Personal Information Protection + Privacy Principle
ISO-25012-5.2Defining data quality measures
JP-AIG-Data-Governance-Training-Data-Quality-Provenance-Lineage-Copyright-APPI-Personal-Information-ProtectionJapan AI Guidelines Data Governance + Training Data Quality + Provenance + Lineage + Copyright Act 2018 Article 30-4 Text Data Mining Exception + APPI 2022 Amendment + Personal Information Protection + Privacy Principle
ISO-25012-5.3Planning and performing data quality evaluations
JP-AIG-Data-Governance-Training-Data-Quality-Provenance-Lineage-Copyright-APPI-Personal-Information-ProtectionJapan AI Guidelines Data Governance + Training Data Quality + Provenance + Lineage + Copyright Act 2018 Article 30-4 Text Data Mining Exception + APPI 2022 Amendment + Personal Information Protection + Privacy Principle

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What are the key differences between ISO/IEC 25012:2008 - Data Quality Model and Japan AI Guidelines?

ISO/IEC 25012:2008 - Data Quality Model has 36 controls across its framework, while Japan AI Guidelines covers 13 controls. Direct mapping analysis identifies 4 overlapping controls (11% coverage). The frameworks diverge most significantly in Inherent and System-Dependent, where 7 ISO/IEC 25012:2008 - Data Quality Model controls have no direct Japan AI Guidelines equivalent.

How many controls map between ISO/IEC 25012:2008 - Data Quality Model and Japan AI Guidelines?

Of 36 total ISO/IEC 25012:2008 - Data Quality Model controls, 4 map directly to Japan AI Guidelines controls — representing 11% coverage. The remaining 32 controls represent compliance gaps requiring additional documentation or compensating controls to satisfy both frameworks simultaneously.

What are the compliance gaps when mapping ISO/IEC 25012:2008 - Data Quality Model to Japan AI Guidelines?

32 ISO/IEC 25012:2008 - Data Quality Model controls have no direct equivalent in Japan AI Guidelines. The highest concentration of gaps is in Inherent and System-Dependent with 7 unmapped controls. These gaps represent areas where additional controls, policies, or documentation must be created to achieve compliance with both frameworks.

Which control domains have the most gaps between ISO/IEC 25012:2008 - Data Quality Model and Japan AI Guidelines?

The domain with the highest gap count is Inherent and System-Dependent (7 gaps). Export the full domain-by-domain gap breakdown via the Professional tier to generate a prioritised remediation roadmap.

This platform provides educational compliance tools, not legal, regulatory, or professional compliance advice. Cross-framework mappings are AI-assisted interpretations and do not reproduce or replace official standards. Framework names and trademarks belong to their respective owners. Consult qualified professionals for your specific compliance requirements. See our Terms of Service.