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 software

Among other things, the algorithm identifies and anonymises (personal) data and confidential (financial) information in documents before they are published, as required by the Open Government Act.

Last change on 16th of May 2024, at 11:52 (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

2017-12

Contact information

cio-office@minfin.nl

Responsible use

Goal and impact

The purpose of the algorithm is to make the way of working within the Woo, more efficient and effective. The impact on citizens and businesses is not significant, as it does not change the outcome. The work of anonymising documents is mainly faster.

Considerations

An advantage of using this algorithm is that (personal) data can be anonymised more efficiently and effectively. That is, anonymisation happens faster and more accurately compared to a completely manual process. As a result, a citizen gets a faster response to the submitted Woo request.

Human intervention

The employee sees which personal data the algorithm has anonymised. These are always still checked by the employee.

Risk management

The risk is limited because an employee always still has to manually assess the result. In addition, the four-eye principle is applied. This means that another employee also checks the results, further limiting the risk.

Legal basis

Woo and AVG

Links to legal bases

  • Woo: https://wetten.overheid.nl/BWBR0045754/2023-04-01
  • AVG: https://eur-lex.europa.eu/legal-content/NL/TXT/HTML/?uri=CELEX:31995L0046

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

The algorithm is trained to identify personal data. The employee enters a document so the process starts. The algorithm suggests (personal) data that should be varnished. The employee manually reviews this to ensure that only necessary data is varnished.

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