Data Management ( data management plan and netCDF/HDF5 file format)
Thursday, 28 November 2024 -
10:00
Monday, 25 November 2024
Tuesday, 26 November 2024
Wednesday, 27 November 2024
Thursday, 28 November 2024
10:00
Open Science and Open Research Data / Data Management Plan
-
Jonathan Dedonder
(
IACCHOS
)
Open Science and Open Research Data / Data Management Plan
Jonathan Dedonder
(
IACCHOS
)
10:00 - 12:00
Room: CYCL09b
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.
13:00
Netcdf and HDF5 file formats for HPC
-
Quentin Glaude
(
ULiège
)
Netcdf and HDF5 file formats for HPC
Quentin Glaude
(
ULiège
)
13:00 - 15:00
Room: CYCL09b
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.