This doctoral thesis reports on an innovative data repository offering adaptive metadata management to maximise information sharing and comprehension in multidisciplinary and geographically distributed collaborations. It approaches metadata as a fluid, loosely structured and dynamical process rather than a fixed product, and describes the development of a novel data management platform based on a schemaless JSON data model, which represents the first fully JSON-based metadata repository designed for the biomedical sciences. Results obtained in various application scenarios (e.g. integrated biobanking, functional genomics and computational neuroscience) and corresponding performance tests are reported on in detail. Last but not least, the book offers a systematic overview of data platforms commonly used in the biomedical sciences, together with a fresh perspective on the role of and tools for data sharing and heterogeneous data integration in contemporary biomedical research.

Nominated as an outstanding PhD thesis by the University of Genoa, Italy Reports on the first, fully JSON-based metadata repository designed for the biomedical sciences Describes the database performance in the case of large datasets, such as next-generation sequencing results Offers a systematic overview of current data repositories for biomedical science Includes supplementary material: sn.pub/extras

Inhalt
Background.- Motivation and State of the Art.- The JSON-based DataModel.- Results: the Integrated Biobanking Use Case.- Results: XTENS 2, a JSON-Compliant Repository.- Discussion.- Conclusions.