The path to open data is marked by a realisation that there is no 'one size fits all' solution – both in terms of data provision and licensing and communication. Each dataset possesses unique attributes, formats, and complexities that demand tailored approaches for better accessibility. Furthermore, datasets grow at different rates, and novel technologies disrupt existing pathways. The central premise of opening data revolves around inclusivity, yet paradoxically, users' needs remain diverse and often contradictory. Our experience has shown that users, from researchers to enthusiasts, exhibit diverse expectations and requirements regarding data access, but even more so data familiarity and processing capabilities. Acknowledging this diversity is crucial to balance open access and the practicalities of efficient data provision.
Tracing the value of open data is also a challenge. How do you ensure you continue to serve users and add societal benefit while demonstrating to funding bodies that there is a need to continue?
The landscape of weather data is remarkably intricate, even amidst collaborative efforts. The weather data continuum, which extends from real-time observations, reanalysis datasets and historical forecasts to high-resolution model outputs on the short-, medium- and long-range timescale, often suffers from disjointedness. Collaborations exist, yet silos persist. Bridging these gaps necessitates interoperability standards and cross-disciplinary collaborations that stitch together disparate data sources into a coherent narrative. Our experiences underscore the significance of aligning technical infrastructures with the overarching goal of unified and accessible weather information.
In user outreach and engagement, targeting familiar faces is a straightforward endeavour. However, the challenge lies in reaching those who remain unknown. How do we extend the benefits of open data to audiences outside our immediate sphere of influence? Once we reach this sphere, how do we ensure we learn from this?
This presentation will highlight some lessons learned in the context of the questions raised in this abstract, as well as identify potential mitigation measures.

