Sprecher
Beschreibung
To ensure FAIR data (Wilkinson et al., 2016: https://doi.org/10.1038/sdata.2016.18), well-described datasets with rich metadata are essential for interoperability and reusability. In Earth System Science, NetCDF is the quasi-standard for storing multidimensional data, supported by metadata conventions such as Climate and Forecast (CF, https://cfconventions.org/) and Attribute Convention for Data Discovery (ACDD, https://wiki.esipfed.org/Attribute_Convention_for_Data_Discovery_1-3).
While NetCDF can be self-describing, metadata often lacks compatibility and completeness needed by repositories and data portals. The Helmholtz Metadata Guideline for NetCDF (HMG NetCDF) Initiative addresses these issues by establishing a standardized NetCDF workflow. This ensures seamless metadata integration into downstream processes and enhances AI-readiness.
The HMG NetCDF Initiative is a collaborative effort across German research centers, supported by the Helmholtz DataHub. It contributes to broader Helmholtz activities (e.g., HMC) to improve research data management, discoverability, and interoperability.
This presentation will outline the key challenges and solutions and their anticipated impact on the geoscientific community. We will present version 1.0 of the NetCDF metadata attribute guidelines, which have been released, as well as the status of our custom NetCDF checker tool for data producers.
| Alternative Track | 5. From Minimum Requirements to FAIR and AI-Ready: Assessing Metadata Quality |
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