To implement the `Findability' of `FAIR', many are now creating catalogues to promote reuse of valuable data and samples. However, isolated development of these di erent catalogues is a large burden and hinders interoperability to pool information together in more comprehensive catalogues. Therefore we compared existing models from many di erent sources and present MOLGENIS/catalogue, a uni ed catalogue application that generalizes best practices from many biobank, population, (rare) disease, and cohort catalogue communities, e.g. BBMRI, RD-connect, LifeCycle, Lifelines, Maelstrom. The resulting model seeks to provide an extensible model to quickly create a new catalogue based on the MOLGENIS software.
Methods We compared catalogue data models from many existing initiatives and standards (MIABIS) and consulted our many stakeholder projects to identify common data structures and elements. Then we implemented a uni ed but modular data model to accommodate the needs of di erent communities using MOLGENIS software suite, optimised for exible data models and independent development of web user interface `apps', to allow `agile development' with frequent releases. A rst version of the uni ed catalogue data model has been created for evaluation. In addition we have de ned a list of user requirements, based on broad community consultation. This `backlog of user stories' is now being prioritized by Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). the stakeholders to create a community supported roadmap for implementation. We designed MOLGENIS/catalogue to be highly con gurable and extensible to attract community contributions in data model extensions, tools and user interfaces. An online Demo of the MOLGENIS catalogue model can be found here: We believe that focus of e orts into one uni ed catalogue application will greatly improve development speed and promote interoperability, and invite the biobank community to feedback and steer its development to meet all their needs. This will help us, to make the model even more useful. We're working with various semantic communities, such as SWAT4HCLS, CINECA, EJP-RD, to improve the semantic enrichment and make cross domain federated searches a reality.