Best practices on data sharing from a service provider perspective

MeteoIQ collects, harmonizes, and processes meteorological data from a wide range of providers, forming the backbone of several operational services. These data sources include in situ weather station observations, numerical weather prediction (NWP) outputs, emerging AI-based forecast products, as well as radar and satellite-derived datasets. The modalities for accessing these data vary considerably. They range from fully unrestricted open-data platforms to restricted or commercial services with heterogeneous licensing schemes, formats, and delivery mechanisms.

Over recent years, the broader shift towards open data in meteorology has created significant opportunities for innovation, interoperability, and downstream service development. At the same time, it has introduced new challenges for service providers. These include inconsistencies in metadata standards, varying levels of data quality control, lack of versioning, and uncertainties related to long-term availability and reliability. Such issues can directly affect the robustness of value-added services and the reproducibility of derived products.

In this contribution, we present a service-provider perspective on best practices for meteorological data sharing. Drawing from our operational experience and the requirements of our users, we identify key principles that facilitate efficient data reuse and integration. These include standardized and well-documented metadata, stable and predictable access interfaces (e.g., APIs), transparent data provenance, clear licensing conditions, and consistent update cycles. We also highlight the importance of communication with data re-users as well as offering prompt and competent operational support.

Furthermore, we discuss how these best practices not only reduce technical barriers but also foster trust and collaboration between data providers and downstream users. By illustrating practical examples from our workflows, we aim to contribute to ongoing discussions on how to make meteorological data more accessible, reliable, and usable for a wide range of applications, from research to commercial services.