AD4GD D4.2 Connecting the Green Deal Data Space (initial)

This document continues the work presented in D4.1 follows the components’ architecture defined by D6.1, focussing primarily on three components: Component 2 – Evaluation of Connector Solutions 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”. Section 2 Evaluation of Connector Solutions discusses the role of data connectors in creating secure and interoperable dataspaces, as highlighted by the International Data Spaces Association (IDSA). AD4GD has implemented an IDSA-aligned data connector, integrated with its repository, to facilitate data sharing across different spaces. This connector allows AD4GD to function as both a data provider, exposing pilot datasets, and a data consumer, integrating external data sources. By adopting IDSA standards, AD4GD aligns itself with broader European data initiatives like Gaia-X and FIWARE, aiming to contribute to a unified data ecosystem. The section also describes an initial evaluation of the connector’s performance through a test scenario involving data exchange between two IDSA-compliant instances-one within the AD4GD space and an external connector acting as a data consumer. This tests demonstrates the potential for seamless data transactions and sets the foundation for further integration in upcoming project deliverables. Section 3 Data Catalogue and Metadata provides an overwiew of the AD4GD data and metadata catalogue implemented in GeoNetwork, focusing on its support for ISO 19115-compliant metadata and integration with other dataspace components. GeoNetwork is utilized for organizing geospatial and environmental datasets, providing structured data access through OGC-compliant services like CSW (Catalogue Service for the Web). The section also describes steps for linking metadata with datasets and integrating quality metrics using QualityML. Section 4 Having laid the groundwork for data catalogue and metadata representations within the project, Section 4: Data Trustworthiness Framework looks at how these tools can be used to implement a framework for tracking data quality and trustworthiness as it flows through each pilot project. This includes the form and prevalence of uncertainty information attached to external datasets used in the project, methods for estimating uncertainty information when it is missing, uncertainty propagation, ground truthing and standardised representations for this information. We analyse the data flow within each pilot project and discuss approaches to each of these questions.