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Efficient and Reliable Data Management for Biomedical Applications.

Ivan Pribec1, Stephan Hachinger1, Mohamad Hayek1

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Summary
This summary is machine-generated.

Modern Research Data Management (RDM) in high-performance computing (HPC) for biomedicine emphasizes FAIR data principles. Projects like CompBioMed and LEXIS demonstrate practical implementation for accessible, resilient data workflows and urgent computing on exascale platforms.

Keywords:
BiomedicineExascaleFAIR principlesHigh-performance computingResearch data managementResilient distributed workflows

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Area of Science:

  • Biomedical research
  • Computational science
  • Data science

Background:

  • Modern research demands robust data management, especially in biomedicine utilizing high-performance computing (HPC).
  • The FAIR data principles (Findable, Accessible, Interoperable, Reusable) are critical for effective RDM.
  • Challenges include data formats, publication, annotation, automated management, HPC infrastructure, and file transfer.

Purpose of the Study:

  • To discuss the challenges and requirements of Research Data Management (RDM) in biomedical applications within high-performance computing (HPC) environments.
  • To highlight the importance of FAIR data principles and practical implementations.
  • To showcase tools and approaches for automated data movement, metadata quality, and resilient workflows.

Main Methods:

  • Discussion of data formats, publication platforms, annotation schemata, and automated data management in HPC.
  • Explanation of data infrastructure, file transfer, and staging methods within HPC centers.
  • Exploration of EUDAT components, ontologies for metadata, and workflow orchestration platforms (e.g., LEXIS, YORC).

Main Results:

  • The CompBioMed project serves as a practical example of implementing RDM principles and tools.
  • The LEXIS project developed an HPC-Cloud convergence platform for Big Data applications, enhancing accessibility.
  • Resilient workflows are achieved through checkpointing, duplicate runs, and data replication, enabling urgent computing.

Conclusions:

  • Effective RDM in biomedical HPC requires adherence to FAIR principles and advanced tools for data management and workflow orchestration.
  • Projects like CompBioMed and LEXIS demonstrate successful integration of these concepts, improving accessibility and enabling urgent computing.
  • The development of ontologies and user-friendly platforms are key to managing complex biomedical data in HPC environments.