Digitalisation has emerged as a “megatrend” in wind energy [1], accelerated by advances in AI technologies and Intelligent Digital Twins [2, 3]. These developments highlight the growing need for interoperability and data sharing across stakeholders. Common, community-adopted information models make data AI-ready by providing a shared vocabulary that defines relationships and semantics, allowing machines to interpret and integrate information consistently. Open innovation [4] is vital for addressing the complex challenges of the energy transition [5] and can be enabled through digital platforms that overcome geographical and organisational boundaries [6]. Such platforms support knowledge exchange in global networks. In wind energy, the WeDoWind open innovation ecosystem provides such a platform, connecting diverse stakeholders to share data, knowledge, and experience openly [4]. WeDoWind brings together four overlapping communities: (1) Information Modelling Community – developing data models, schemas, taxonomies, and ontologies; (2) Collaborative Problem-Solving Community – exchanging knowledge through WeDoWind challenges and sharing teaching materials; (3) Open Data and Code Community – creating guidelines and best practices for publishing open code and data; (4) Data Users’ Community – developing resources and best practices for applying data and code. Several WeDoWind challenges have already been documented in the literature, showing the ecosystem’s potential to reduce costs and increase the value of wind energy [4, 7, 8]. This work introduces the WeDoWind EAWE Test Turbines Committee Space, which hosts new datasets from EAWE Test Turbines Committee members alongside the EAWE Data Science Challenge 2024–2025. We show how these initiatives strengthen open innovation, open science, and open data practices in wind energy, demonstrating how collaborative digital platforms can accelerate the sector’s digital transformation.