Speakers
Description
NetCDF is one of the most widely used scientific data formats in E&E sciences, yet metadata quality, completeness, and interoperability remain highly heterogeneous across institutions, disciplines, and data infrastructures. While standards such as CF Conventions, ACDD, and DataCite provide important foundations, their implementation often varies significantly, limiting data reuse, interoperability, and integration into automated and AI-driven workflows.
The HMG NetCDF initiative addresses this challenge by developing community-driven metadata guidelines for the Helmholtz E&E domain. Following the first guideline release, HMG NetCDF 2.0 focuses on transforming the guidelines into a living standard supported by an active community, implementation tools, and sustainable governance.
This talk presents the vision and planned activities of HMG NetCDF 2.0. We introduce its three pillars: guideline evolution, technical implementation, and community building. The initiative extends metadata recommendations with emerging concepts such as provenance, data quality indicators, and AI-readiness criteria. In parallel, a modular validation ecosystem is being developed to support automated metadata quality assessment and integration into research workflows, repositories, and continuous integration environments. Strong emphasis is placed on user-centred design, community engagement, and reusable metadata profiles that lower adoption barriers for researchers, data managers, and infrastructures.
Beyond enhancing metadata quality and interoperability for NetCDF, HMG NetCDF 2.0 aims to establish a foundation for machine-actionable and AI-ready data ecosystems. The initiative will assess the transferability of metadata profiles, validation approaches, and governance mechanisms to other scientific data formats, such as Zarr and HDF, and to frameworks including RO-Crate and the Helmholtz Knowledge Graph, contributing to metadata harmonisation across infrastructures and disciplines.