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Cross-section project D: Data management platform

Lisa Bald, Kristian Peters, Alexander Goesmann, Thomas Nauss, Dirk Zeuss

To investigate the principles of the interactions between microorganisms, oak trees, and their biotic and abiotic environment, a wide variety of experimental data and metadata must be collected along spatial and temporal scales. These data will be combined in a common research data management platform, addressing the needs for (i) data and metadata description, (ii) data interoperability and (iii) data analysis, and is guided by FAIR principles. Workflow management systems will be used to implement automated workflows for reproducible data analysis. These workflows are to be recorded in a workflow register which, in addition to the registration and versioning of workflows, also allows direct connection to the above-mentioned data management platforms. Requirements regarding data security and permissions will be taken into account.

The IT infrastructure consists of memory components and a CPU (Central Processing Unit) and GPU (Graphics Processing Unit) cluster powerful enough to support big data processing and Deep Learning. The research data platform combines the experience of the project teams and ensures a long-term maintenance and availability perspective through close integration with existing institutional solutions.