Rulebook Template
Validation & Verification Rulebook Template for Data Models
## 1. Goal of this `<<YOUR_USECASE>>` Rulebook
Describe the purpose of this rulebook.
Example:
This rulebook establishes clear validation and verification criteria to ensure data integrity, consistency, and trustworthiness for [Insert Data Model or Use Case]. It supports all stakeholders in aligning with shared expectations for data quality and regulatory compliance.
---
## 2. Why is Data Trust Necessary in the `<<YOUR_USECASE>>` Use Case ?
Explain the importance of data trust within your use case:
Example Benefits:
- Improves data-driven decision-making
- Reduces operational risks
- Supports compliance and audit readiness
- Enhances supply chain transparency
- Enables interoperability between systems
---
## 3. Business Value of Validated Data
List the business benefits of applying this rulebook.
Example Benefits:
- Enhanced transparency for stakeholders
- Improved regulatory compliance
- Streamlined internal processes through validated data
- Increased customer and partner trust
---
## 4. Scope of this Rulebook
Define the scope of the data validation covered (e.g., systems, datasets, lifecycle phases).
Example Scope:
- Data domains: [Product, Supplier, Compliance, etc.]
- Validation types: [Syntax, Semantic, Consistency, Completeness]
- Applicable lifecycle stages: [Creation, Exchange, Use, Archiving]
---
## 5. Definitions & Terminology
| Term | Definition |
|--------------|----------------------------------------------------|
| Verification | Confirms data was created according to standards. |
| Validation | Assesses whether data is logical, reasonable, and fit-for-purpose. |
| [Additional] | [Insert definition] |
---
## 6. Validation Rules by Data Category
Each data category includes attribute-level rules for validation and verification.
Include here the sections of your data model which require content validation.
### `<Attribute Section 1>`
| Rule ID | Attribute | Description | Mandatory/Optional | Validation Rule | Data Type |
|---------|--------------|--------------------|--------------------|-------------------------|-----------|
| 1.1 | `<attribute name>` | `<description>` | `<Mandatory/Optional>` | `<regex pattern>` | `<String,Integer,...>`|
### `<Attribute Section 2>`
| Rule ID | Attribute | Description | Mandatory/Optional | Validation Rule | Data Type |
|---------|--------------|--------------------|--------------------|-------------------------|-----------|
| 2.1 | `<attribute name>` | `<description>` | `<Mandatory/Optional>` | `<regex pattern>` | `<String,Integer,...>`|
---
## 7. References & Standards
List the legal, technical, or industry standards your rules align with (e.g., ISO 9001, ISO 14067, GDPR).
---
## 8. Future Extensions / Next Versions
Optionally, describe planned updates or areas for extension.
---
## Appendix
Include any diagrams, flows, or supporting materials.
---
## Usage Instructions
1. Adapt this template to your specific data model.
2. Populate tables with relevant attributes and validation logic.
3. Version and maintain this document to support audit and governance processes.
NOTICE
This work is licensed under the CC-BY-4.0.
- SPDX-License-Identifier: CC-BY-4.0
- SPDX-FileCopyrightText: 2025 Contributors to the Eclipse Foundation
- SPDX-FileCopyrightText: 2025 Fujitsu Limited
- SPDX-FileCopyrightText: 2025 Robert Bosch GmbH
- SPDX-FileCopyrightText: 2025 Spherity GmbH
- SPDX-FileCopyrightText: 2025 Schaeffler AG
- SPDX-FileCopyrightText: 2025 SIEMENS AG
- SPDX-FileCopyrightText: 2025 Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V. (represented by Fraunhofer IPK)
- SPDX-FileCopyrightText: 2025 CGI Deutschland B.V. & Co. KG
- SPDX-FileCopyrightText: 2025 TÜV SÜD Auto Service GmbH
- SPDX-FileCopyrightText: 2025 BASF SE
- SPDX-FileCopyrightText: 2025 BMW AG
- SPDX-FileCopyrightText: 2025 Cofinity-X GmbH
- SPDX-FileCopyrightText: 2025 Henkel AG & Co. KGaA
- Source URL: https://github.com/eclipse-tractusx/eclipse-tractusx.github.io