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.

Anonymisation tool

anonymisation tool

Last change on 15th of January 2025, at 7:18 (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

01-2024

Contact information

Gemeente Achtkarspelen, gemeente@achtkarspelen.nl

Link to publication website

www.achtkarspelen.nl

Responsible use

Goal and impact

The municipality wants to be transparent to its residents and entrepreneurs, but it also has to comply with privacy legislation, among other things. The deployment of anonymisation software makes this possible by supporting employees in anonymising documents.

Considerations

The use of anonymisation software speeds up and simplifies the process for active and passive disclosure. Automated anonymisation is also less error-prone than human intervention. This reduces the risk of a data leak and better protects the data of residents and entrepreneurs

Human intervention

A staff member reviews the anonymisation software proposal before it is made final.

Risk management

The risks are minimal because an employee is always still assessing the result.

Legal basis

General Data Protection Regulation (AVG), General Data Protection Regulation Implementation Act (UAVG) and Open Government Act (Woo), Electronic Publication Act (WEP).

Links to legal bases

  • AVG: https://wetten.overheid.nl/BWBR0011468
  • UAVG: https://wetten.overheid.nl/BWBR0040940
  • Woo: https://wetten.overheid.nl/BWBR0045754
  • Wep: https://wetten.overheid.nl/BWBR0043961

Operations

Data

This depends on the document being anonymised. Examples include personal data such as e-mail addresses, phone numbers, bank account numbers, address details and signatures. And based on the Open Government Act (Woo), it can also include data beyond personal data. These grounds for exception are listed in the Woo.

Technical design

Smart features, such as set rules or templates, make it possible to anonymise per document or as a bulk. In this way, the method and degree of anonymisation of commonly used (standard) documents can also be set. The software then uses pattern recognition and Natural Language Processing to search for names, addresses, dates of birth, specific set words, signatures or regular expressions (such as e-mail, IBAN, BSN). The DataMask software recognises these and makes suggestions to mask or anonymise them fully automatically.

External provider

XXLLNC

Similar algorithm descriptions

  • Application to anonymise documents

    Last change on 21st of November 2024, at 10:43 (CET) | Publication Standard 1.0
    Publication category
    Other algorithms
    Impact assessment
    Field not filled in.
    Status
    In use
  • Application to anonymise documents

    Last change on 11th of June 2024, at 11:41 (CET) | Publication Standard 1.0
    Publication category
    Other algorithms
    Impact assessment
    Field not filled in.
    Status
    In use
  • Anonymising documents for publication or provision

    Last change on 19th of December 2024, at 13:43 (CET) | Publication Standard 1.0
    Publication category
    Impactful algorithms
    Impact assessment
    DPIA
    Status
    In use
  • The algorithm recognises and anonymises personal data in documents.

    Last change on 7th of August 2024, at 9:45 (CET) | Publication Standard 1.0
    Publication category
    Other algorithms
    Impact assessment
    DPIA
    Status
    In use
  • Recognising and anonymising privacy-sensitive information

    Last change on 13th of June 2024, at 13:21 (CET) | Publication Standard 1.0
    Publication category
    Other algorithms
    Impact assessment
    Field not filled in.
    Status
    In use