glam/schemas/20251121/linkml/modules/classes/DataSensitivityLevel.yaml
kempersc 6bb8ac20ba feat: Add MainPart and OutputData classes with detailed specifications
- Introduced MainPart class to represent principal portions with quantified values, including attributes for part type and currency code.
- Added OutputData class to specify output characteristics from devices/services, including format, description, and destination URL.
- Created canonical_value, capacity, capacity_type, and capacity_value slots for enhanced data representation.
- Archived and migrated various slots related to data sensitivity, dataset descriptions, and titles to align with new structures.
- Implemented has_or_had_caption and has_or_had_main_part slots to support media accessibility and primary portion representation.
- Enhanced data license policy slot to define custodian data licensing and openness policies.
2026-01-23 11:04:15 +01:00

117 lines
4.7 KiB
YAML

id: https://nde.nl/ontology/hc/class/DataSensitivityLevel
name: data_sensitivity_level_class
title: DataSensitivityLevel Class
description: >-
Data sensitivity classification level for records and information assets.
Used to categorize the confidentiality requirements and access restrictions
for administrative records, documents, and data systems.
Based on common information classification schemes including:
- ISO 27001 information security standards
- GDPR special category data requirements
- Dutch government classification (Rijksoverheid)
prefixes:
linkml: https://w3id.org/linkml/
hc: https://nde.nl/ontology/hc/
dcterms: http://purl.org/dc/terms/
schema: http://schema.org/
imports:
- linkml:types
- ../slots/has_or_had_label
- ../slots/has_or_had_description
- ../slots/has_or_had_short_code
default_prefix: hc
classes:
DataSensitivityLevel:
class_uri: hc:DataSensitivityLevel
description: >-
Data sensitivity classification level.
**Standard Classification Levels**:
| Level | Short Code | Description | Access |
|-------|------------|-------------|--------|
| Public | PUBLIC | No restrictions on disclosure | Anyone |
| Internal | INTERNAL | For internal use only | Staff only |
| Confidential | CONFIDENTIAL | Need-to-know basis | Authorized staff |
| Strictly Confidential | STRICTLY_CONFIDENTIAL | Highly restricted | Named individuals |
| Personal Data | PERSONAL_DATA | Contains PII (GDPR Article 6) | Data subjects + authorized |
| Special Category | SPECIAL_CATEGORY | Sensitive personal data (GDPR Article 9) | Strictly controlled |
**GDPR Alignment**:
- PERSONAL_DATA: Covers GDPR Article 6 personal data
- SPECIAL_CATEGORY: Covers GDPR Article 9 special categories (health, religion,
ethnicity, political opinions, trade union membership, genetic/biometric data,
sexual orientation)
**Dublin Core**: Maps to dcterms:accessRights for access classification.
exact_mappings:
- dcterms:accessRights
close_mappings:
- schema:accessMode
slots:
- has_or_had_label
- has_or_had_short_code
- has_or_had_description
slot_usage:
has_or_had_label:
description: Human-readable name for the sensitivity level.
range: string
required: true
examples:
- value: "Public"
description: No access restrictions
- value: "Strictly Confidential"
description: Highest restriction level
has_or_had_short_code:
description: >-
Short code identifier for the sensitivity level.
Standard codes: PUBLIC, INTERNAL, CONFIDENTIAL, STRICTLY_CONFIDENTIAL,
PERSONAL_DATA, SPECIAL_CATEGORY
range: string
required: true
pattern: "^[A-Z][A-Z0-9_]*$"
examples:
- value: "PUBLIC"
description: No restrictions
- value: "CONFIDENTIAL"
description: Need-to-know basis
- value: "SPECIAL_CATEGORY"
description: GDPR Article 9 sensitive data
has_or_had_description:
description: Detailed description of what this sensitivity level means and when to apply it.
range: string
required: false
examples:
- value: "Contains employee health records - requires explicit consent and strict access controls"
description: SPECIAL_CATEGORY example
annotations:
specificity_score: 0.45
specificity_rationale: >-
Data sensitivity levels are moderately specific - used primarily in
records management and information governance contexts.
custodian_types: '["A", "O", "R"]'
custodian_types_rationale: >-
Most relevant for Archives (A), Official institutions (O), and
Research centers (R) that manage sensitive records.
examples:
- value:
has_or_had_label: "Confidential"
has_or_had_short_code: "CONFIDENTIAL"
has_or_had_description: "Need-to-know basis - restricted to authorized personnel"
description: Standard confidential classification
- value:
has_or_had_label: "Special Category Data"
has_or_had_short_code: "SPECIAL_CATEGORY"
has_or_had_description: "GDPR Article 9 sensitive personal data - health records, religious affiliation"
description: GDPR special category classification
- value:
has_or_had_label: "Personnel Data"
has_or_had_short_code: "PERSONAL_DATA"
has_or_had_description: "Contains employee personal information subject to GDPR"
description: Personal data classification for HR records