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In modern dataspaces, accessing and using data from providers should be straightforward, but technical barriers often prevent non-technical users from taking full advantage of available data. Data consumers face challenges in composing complex REST calls with specific parameter formatting requirements, and retrieved data may not match their expected schema or format. This is where the DS2 RET (Data Retrieval) module comes in. What is RET? RET is an intelligent data retrieval

Joining a dataspace is supposed to unlock data, not bury participants in decisions. Yet for many organisations the first encounter with a federated environment looks less like an open door and more like a wall of questions. Which modules do I actually need? Are my two dataspaces even compatible for the workflow I have in mind? What does the regulation require of me before I share a single record? And once I have the answers, how do I configure everything correctly without a s

How do you get farmers, processors, public institutions, and environmental agencies to share data, when competitive sensitivity, power asymmetries, and data sovereignty concerns stand in the way? In Slovenia's Pomurje region, the DIH AGRIFOOD Data Space (DADS) has been answering that question in practice, as part of the Horizon Europe DATA4FOOD project and in direct collaboration with the DS2 project. The Slovenian use case within DS2 focuses on air quality monitoring across