Template
EU AI Act Article 10 - Data and Data Governance Template
Article 10 is where teams explain how training, validation, and testing data are governed for the relevant AI system. The reviewer needs a clear written account of where data comes from, how relevance and possible bias are examined, and how data preparation is controlled.
Technical contribution: Evidence-backed scaffold
Who supplies what
What Article 10 expects, what the toolkit can add, and what your team still owns
This page is a drafting scaffold for the Article 10 section. It helps structure the writing, but your team still has to supply the system-specific data-governance details required by law.
| Article 10 expects | What the template can add | What your team still has to write | Practical output to keep |
|---|---|---|---|
| Data governance and management practices | A law-shaped section for training, validation, and testing data governance. | Describe the actual governance and management practices used for the relevant AI system. | A written Article 10 section in the package. |
| Data origin and collection process | Prompts for data origin and collection inputs. | State where the data comes from and how it is collected for this system. | A short source-and-collection note. |
| Checks for relevance, representativeness, bias, and errors | A draft structure for these required checks. | Record the checks actually performed and the main findings. | A review note or summary table for the data set. |
| Data preparation operations | A place to describe the processing operations used before model work or testing. | List the actual cleaning, labeling, filtering, transformation, or augmentation steps used. | A concise data-preparation summary. |
Manual fields
What your team still adds to Article 10
Article 10 remains system-specific. The template can structure the section, but it cannot infer your data source, sampling logic, quality checks, or bias review from the package alone.
| What you add | Why it is required | Practical format to use |
|---|---|---|
| Data source description | The section must describe the origin of the data used for the relevant AI system. | A short paragraph naming the source, scope, and collection channel. |
| Representativeness and relevance review | The section must explain why the data is relevant and sufficiently representative for the intended purpose. | A short written assessment or review table. |
| Bias and data-quality checks | The section must record what checks were done for possible bias and errors. | A checklist or narrative summary of the checks and findings. |
| Data preparation summary | The section must describe the main preparation operations used before training, validation, or testing. | A short sequence of named preparation steps. |
FAQ
Frequently asked questions
What is the Article 10 - Data and Data Governance template page for?
This page explains what the Article 10 - Data and Data Governance template section usually needs to cover inside an EU AI Act package, which parts can be supported by structured evidence, and which parts remain owned by the provider, deployer, or legal reviewer.
Does this Article 10 - Data and Data Governance template page create a complete EU AI Act package?
No. It is one section-level guide. A review-ready package still needs the selected role and scope, the other applicable article-level sections, linked technical evidence, owner completion, and final human review.
What evidence should be linked to the Article 10 - Data and Data Governance template section?
Use evidence that is current, traceable to the relevant system version, and connected to real runs, retained records, or approved procedures. A weak package relies only on narrative text; a stronger package links the narrative to reproducible artifacts.
Who should review the Article 10 - Data and Data Governance template section before handoff?
The technical owner should confirm the system facts and evidence links, while compliance or legal reviewers confirm whether the section is sufficient for the selected EU AI Act role, scope, and conformity path.