Mainzelliste

Mainzelliste is a web-based open source pseudonymization software which was originally designed at Mainz University Medical Center and now is actively developed by the members of Mainzelliste community under the leading of the Federated Information Systems working group from DKFZ, Heidelberg. It allows the generation of the pseudonyms (PID) from the identifying fields (IDAT) even if the identifying data has errors. Mainzelliste methods are accessed through can be accessed through the REST interface, which allows an easy integration within other tools.

Main functionality of Mainzelliste:

• Pseudonym generation – substitution of identifying personal data with the string not related to the original data

• Record Linkage – for each patient there is only one pseudonym of a certain type which is generated, even if there are small errors in the identifying data. Near the record linkage based on the raw identifying data, Mainzelliste also allows the privacy preserved record linkage based on the irreversibly transformed identifying fields and the secure multiparty computation where the identifying data never leaves the storage.

• REST Interface – allows the connection of Mainzelliste to different systems, such as registrys, biobanks, EDC and study management systems.

• Graphical interface – allows easy use of Mainzelliste functions without showing the complex workflow behind them.

• Backward compatibility

• Audit Trail

To get start with Mainzelliste you can watch our Tutorial Video: [ NFDI ToolTalk: Mainzelliste. Pseudonymization and Record Linkage Tool. (10 November 2021) - YouTube ] . For more details about Mainzelliste please take a look at our repository: [ mainzelliste.de ] . For Mainzelliste GUI please use: [ https://github.com/medicalinformatics/mainzelliste-gui/ ]. To cite Mainzelliste please use the following publication:

Lablans M, Borg A, Ückert F. A RESTful interface to pseudonymization services in modern web applications. BMC Medical Informatics and Decision Making 2015, 15:2. http://www.biomedcentral.com/1472-6947/15/2

For learning more about Mainzelliste in combination with Secure Multiparty computation please take a look at the following publications:

Stammler et al. Mainzelliste SecureEpiLinker (MainSEL): Privacy-Preserving Record Linkage using Secure Multi-Party Computation. Bioinformatics 2020

Kussel, Tobias et al. (2022): Record linkage based patient intersection cardinality for rare disease studies using Mainzelliste and secure multi-party computation. In: Journal of translational medicine 20 (1), S. 1–14. DOI: 10.1186/s12967-022-03671-6.