The VerbIS department develops IT-support methods for researchers who want to collaborate across multiple locations. To this end, concepts and tools are developed for recurring problems in medical informatics, used in multicentric collaborative projects and finally published as open source software under the name Samply.


A Metadata Repository (MDR) provides a structured comparable definition with respect to the meaning of the data to be exchanged, laying the foundation for multicentric data integration. The Samply.MDR software, which is based on the ISO 11179 standard, was developed for this purpose.


A bridgehead (Samply.Share) allows the local, metadata-supported consolidation of data and cooperation with research alliances through networking with search services. A special form of federated search services, decentralized search, allows participation in alliances without disclosing sensitive data.

  • Lablans M, Kadioglu D, Mate S, Leb I, Prokosch H-U, Ückert F (2016) Strategien zur Vernetzung von Biobanken. Klassifizierung verschiedener Ansätze zur Probensuche und Ausblick auf die Zukunft in der BBMRI-ERIC. Bundesgesundheitsblatt 59(3): 373–378. Open Access verfügbar
  • Lablans M, Kadioglu D, Muscholl M, Ückert F (2015) Exploiting Distributed, Heterogeneous and Sensitive Data Stocks while Maintaining the Owner's Data Sovereignty. Methods Inf Med 54(4): 346–352. Open Access verfügbar

Data protection

To consolidate patient data across multiple institutions while ensuring data protection requirements, the Mainzelliste was developed, a web-based pseudonymization service of the first level with support for record linkage.

  • Lablans M, Borg A, Ückert F (2015) A RESTful interface to pseudonymization services in modern web applications. BMC Med Inform Decis Mak 15: 2. Open Access verfügbar

Multi-centre data acquisition / registers

The Open Source Register System for Rare Diseases (OSSE) combines all the above mentioned Samply components and the main cell list with a user administration and an interface for Electronic Data Capture (Samply.EDC) and is therefore suitable for the flexible creation and application of input masks for the multi-centric, structured documentation of clinical facts.


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