A DSGA should be supported to ensure the development and ongoing maintenance of the common open-source building blocks, as outlined in this blueprint. All stakeholders have emphasized the necessity for collaborative efforts in developing and funding these building blocks to prevent redundant development endeavours. Under the CLOUD-AI call, the EDGE-Skills project led by Prometheus-X, is dedicated to funding the development of all the building blocks listed in this blueprint.
However, relying solely on open-source implementations proves insufficient. A comprehensive approach requires the establishment of products and dedicated teams to operate them, essentially providing Data Intermediary Services through digital products by leveraging the open-source building blocks. To ensure trust and compliance, the Data Space Governance Authority (DSGA) should certify trusted Data Intermediaries, ensuring their operation aligns with the prescribed building blocks and fosters interoperability. This approach offers data space participants a choice of providers, eliminating the need for a single, compulsory provider selection while ensuring interoperability and data sharing across the data space.
By simultaneously ensuring the development of essential building blocks and certifying trusted data intermediaries, such a DSGA will pave the way for the implementation of a distributed, open, and trusted data space infrastructure.
Furthermore, the DSGA’s organizational structure should be non-profit, featuring a governance model that allows members to make decisions regarding which building blocks to develop based on specific criteria. Additionally, it should adopt a business model, possibly cantered around data intermediary certification, to facilitate the creation of open-source reference implementations of these models. This approach guarantees the continuity of the skills data space with a dedicated structure and sustainable business model. Prometheus-X is set up as a non-profit with such a governance and business model.
These recommendations are pivotal for the growth and successful deployment of the skills data space for several reasons. Firstly, they serve to reduce costs and eliminate barriers that might impede participation. Secondly, they establish and maintain trust within the ecosystem. Thirdly, they ensure the continuity of operations, preventing disruptions. Lastly, they foster cohesion and collaboration within the community, promoting collective progress and innovation.
