NFDI4Ing
Published April 15, 2024 | Version v1
Presentation Open

Workshop: Research Data Management for Data from High Performance Computing (tier 1) – Best-Practice and Applications

Creators

  • 1. Technische Universität München
  • 2. ROR icon Leibniz Supercomputing Centre
  • 3. Universität Stuttgart Höchstleistungsrechenzentrum Stuttgart
  • 4. ROR icon Technical University of Munich

Description

This workshop will introduce researchers to the basics of research data management (RDM) as well as tools and systems available at different (tier 1) HPC centers. It shows techniques on how to structure, document and publish your research data and which tools and resources can support you.  You will earn knowledge of tools and services for data and metadata collection, storage, publication and transfer of large data.

This supports bookkeeping in your own research, exchange with colleagues in your group and dissemination and use of research data with external partners. Publishing research data along journal publications will soon become commonplace and will allow for a wider range of use of comparative research data within the course of your PhD.

Topics:

  • Hardware systems, storage systems, data transfer tools at the different HPC centers (e.g. SuperMUC-NG, Hawk, JUWELS & JURECA), backup and archiving, UFT, GridFTP, Globus Online, data containers (e.g. LRZ DSS)
  • Research data management tools and services for data from HPC: Metadata standards, metadata crawling, cloud storages, interfaces, repositories, containerization, FAIR HPC data, B2SHARE, InHPC-DE etc.
  • Basics in research data management: FAIR data principles, metadata & terminology, repositories, identifier (DOI), licenses, best-practice

Notes (English)

The authors and speakers would like to thank the Federal Government and the Heads of Government of the Länder, as well as the Joint Science Conference (GWK), for their funding and support within the framework of the NFDI4Ing consortium. Funded by the German Research Foundation (DFG) - project number 442146713.

The authors would also like to thank the Competence Network for Scientific High Performance Computing in Bavaria (KONWIHR) for their funding and support within a short term project.

Files

1_General_RDM_and_FAIR_principles_TUM.pdf

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