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
- Organisation
- Municipality of Someren
- Theme
- Organisation and business operations
- Status
- In use
General information
Name
Short description
Organisation
Theme
Status
Begin date
Contact information
Link to publication website
Publication category
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, as a staff member 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
Links to impact assessment
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.
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.