This document presents the final form of the work done in WP 4 and previously partially presented in D4.1 and D4.2, the Dataspace architecture, the data catalogue and metadata system and the data trustworthiness framework. Like in D4.2, the text follows the components’ architecture defined by D6.1, focussing primarily on new work done since D4.2:

Component 2 – Evaluation of Connector Solutions and Deployments
Component 9 – Data catalogue and Metadata
Component 11 – Data Trustworthiness Framework

In terms of tasks, this deliverable predominantly discusses work in WP4 “Satellite and Green Deal Data Space Integration”, including tasks 4.2 “Green Deal Data Space Implementation”, 4.3 “Green Data Space integration with third-party services” and 4.4 “Ground truthing and data trustworthiness framework”. It also has overlap with and incorporates work from the three pilot projects within WP6 and the machine learning work being done in WP5.

This deliverable builds upon D5.1 and outlines progress in applying Artificial Intelligence and High-Performance Computing within the AD4GD project. It details the use of AI models in pilot studies, such as water level prediction in Berlin lakes and connectivity mapping in Catalonia, highlighting the AI models ability to process complex environmental data efficiently. The document also presents the development of user-friendly interfaces that make these advanced tools accessible to non-expert stakeholders, promoting informed decision-making. Additionally, it reports on the integration of HPC resources to support AI model training and execution, enhancing performance and scalability. The deliverable concludes with reflections on the benefits, limitations, and future directions of these technologies in AD4GD pilots.