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

Identifying and anonymising privacy-sensitive information in information objects (in many cases, documents).
Last change on 1st of July 2026, at 7:04 (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

2022-01

Contact information

info@noordoostpolder.nl

Link to publication website

https://noordoostpolder.nl/privacy

Responsible use

Goal and impact

The aim of the algorithm is to anonymise privacy-sensitive information contained in data objects. This protects personal information and safeguards individuals’ privacy.

Considerations

The algorithm has been trained to recognise privacy-sensitive information, but is limited to classification and will therefore never reveal any substantive information. Furthermore, the technology helps to improve the quality of anonymisation.

Human intervention

The results produced by the algorithm serve merely as a tool; human intervention is always required for the final anonymisation.

Risk management

To mitigate the privacy risks posed by the algorithm, it undergoes constant evaluation and updates to address new threats and privacy challenges. Human oversight and intervention are built into the system to correct errors. Furthermore, there is an ongoing dialogue with stakeholders.

Legal basis

General Provisions on Environmental Law Act (Wabo)
Open Government Act (WOO)
General Administrative Law Act (Abw)

Operations

Data

It is possible to populate lists of values specifying which data should not be visible and which should be visible.

Technical design

Deep learning models that determine, on the basis of both visual and textual data, which information is considered privacy-sensitive.

External provider

eData / eSpecialists

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