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DataCastle: A Pragmatic Approach for Research and Real-World Data Management
Jori Kern1,2,3,4,5, Markus Katharina Brechtel6,7, Tim Schumacher1,2,3,4,5
1Federated Information Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Abstract:
Effective research data management (RDM) is essential for ensuring transparency, reproducibility, and collaboration in biomedical research, yet heterogeneous clinical and experimental data challenges fragmented infrastructures. DataCastle is a modular open-source platform that bridges FAIR data acquisition and FAIR data use by integrating enrollment-time pseudonymization, metadata extraction and background versioning of data and a processing environment for data analysis. Structured data are captured via an EDC system, unstructured data are stored within a filesystem-based data lake and metadata are mapped to Health DCAT-AP to support findability and EHDS alignment. DataCastle connects managed data to analysis and visualization tools to enable reproducible and version-linked workflows.
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