Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.

Anonymise

Searching and anonymising (deleting) personal information. In many cases, this involves information in documents and/or e-mails.

Last change on 22nd of September 2025, at 9:36 (CET) | Publication Standard 1.0
Publication category
Other algorithms
Impact assessment
Field not filled in.
Status
In use

General information

Theme

Organisation and business operations

Begin date

01-2023

Contact information

postbus@noordenveld.nl

Responsible use

Goal and impact

We use the computer programme to wipe out personal data from documents before making them public. With this programme, it is faster and more efficient than if we do it ourselves.

Considerations

We increasingly need to disclose information. Then it is important to lacquer away personal and sensitive information in advance. Not only is the programme easier and better than doing it ourselves, but it also leads to fewer errors. This reduces the chance of data ending up where it does not belong, and citizens' and companies' data are better protected.

Human intervention

An employee of the municipality determines which documents are processed in this programme. Then the employee checks the results. Thus, the programme is mainly used as a tool.

Risk management

The programme is regularly updated. This way, the programme continues to protect personal data even as new risks or threats arise. There are people monitoring this and fixing problems.

Legal basis

Open Government Act

Electronic Publications Act

General Data Protection Regulation

Links to legal bases

  • Open Government Act (WOO): https://wetten.overheid.nl/BWBR0045754/
  • Electronic Publications Act (WEP): https://wetten.overheid.nl/BWBR0043961/
  • General data protection regulation (AVG): https://wetten.overheid.nl/BWBR0041233/2023-11-01

Operations

Data

All information carriers entering and leaving the municipality.

Technical design

Deep learning models that determine in both visual and textual ways what information is considered privacy-sensitive.

External provider

eData B.V.

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