Navigating the International Data Space To Build Edge-Driven Cross-Domain Dataspace Ecosystem

Data is an asset for the modern industrial era that plays a crucial role in driving intelligence through machine learning techniques and methods for business, technical, economic, and social decision making. Generally, data generated in a specific domain is often used in other domains, which requires cross-domain data integration (CDDI) and sharing across edges. Here, an edge represents an organization, system, or entity with computing data processing capabilities. This CDDI and sharing across edges need data sovereignty to govern the relevant usage context, wherein the sharing edge domain’s data context must be respected by the shared edge domain. This edge domain’s data context can be seen as a medium to define rules for associated data usage, access, and identity management. This can be achieved by the common dataspace vision of the European Union for CDDI to turn the European market into a unified data-driven European market. International Data Space (IDS) is such an effort backed up by the European Commission to develop relevant standards and specifications for CDDI. However, even though a vast amount of IDS ecosystem information is available online, it is scattered and hard to navigate. This obstructs the use and adoption of the IDS at a desired pace and in a simplified manner. This study contributes to this need by converging the information in one place and leveraging theoretical and pragmatic insights on building IDS-based edge-driven dataspace in real-world scenarios. We dive into a wind industry supply-chain-specific use case realized through a locally developed IDS platform to showcase and validate the use of CDDI.