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Data Management ( data management plan and netCDF/HDF5 file format)

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CYCL09b (Louvain-La-Neuve)

CYCL09b

Louvain-La-Neuve

chemin du Cyclotron 2, 1348 Louvain-La-Neuve
Description
All HPC program will produce or consume data at a point or another.
Where to write/store those data during and after your program is finished is important both in term of efficiency and in term of data preservation (which is important due to the growing relevance of Open Science)

Contents:

  • Introduction to data storage and access
  • The netcdf/hdf5 file format
  • Open Science and Open Research Data / Data Management Plan

Prerequisite: None

Type: presentation, discussions and hands on


Must: This session is a must have for researchers concerned by the dissemination of research results and by their impact.
Registration
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23 / 50
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    • 1
      Open Science and Open Research Data / Data Management Plan

      The growing relevance of Open Science poses challenges to research practices. Open Research Data, which aims to provide free access to research data in order to ensure the reproducibility of scientific results, is one important aspect of Open Science. Research Data Management (RDM), on its side, addresses the entire life cycle of data, covering planning, collection, management, storage, publication, referencing, preservation and sharing of research data, as well as access and reuse rights.

      This seminar addresses concerns of openness, covers the integration of open Data/FAIR Data into research data management principles as well as practical aspects such as the publication of data in repositories.

      Speaker: Jonathan Dedonder (IACCHOS)
      2023 01 24 RDM _ Jonathan Dedonder _ 1 by Page.pdf
      2023 01 24 RDM _ Jonathan Dedonder _ 3 by Page.pdf
      DMP online
    • 2
      Netcdf and HDF5 file formats for HPC

      Description:
      This seminar provides a practical introduction to NetCDF and HDF5, two key structured data formats for scientific data management. Participants will learn to create, manipulate, and visualize these formats using Python, Fortran, and C, with a focus on their application in high-performance computing environments.

      Contents:

      • Overview of data formats in Sciences
      • Comparing NetCDF vs HDF5
      • Tools and libraries for working with NetCDF and HDF5
      • Use cases in scientific research and HPC
      • Hands-on exercises in creating, reading, and visualizing data

      Prerequisite:

      • Being able to connect to the clusters.
      • Basic programming skills (Python, Fortran, or C).
      • Familiarity with Linux (navigation, file creation and editing).

      Target audience:
      Researchers and data scientists using HPC systems.

      Must for:
      Essential for geoscientists, or anyone needing structured and efficient data format.

      Speaker: Quentin Glaude (ULiège)
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