Interoperability architecture for data spaces.

Area of Science:

• Computer Science
• Information Science
• Distributed Systems

Background:

• Data spaces are emerging as crucial infrastructure for secure data sharing.
• Existing data spaces often face interoperability challenges due to technological heterogeneity.
• There is a need for a standardized architecture to facilitate cross-data space data exchange.

Purpose of the Study:

• To propose and validate a novel interoperability architecture for data spaces (DSIA).
• To enable secure and efficient data sharing among members of different data spaces, irrespective of their underlying technologies.
• To reduce governance overheads and simplify deployment for existing data space participants.

Main Methods:

• Development of a four-component interoperability architecture: data sharing sub-systems, data pipeline, deployment, and supporting applications.
• Leveraging existing trust mechanisms within data spaces and extending them with shared agreements and federation services.
• Validation through DS2 implementations and comparative analysis with alternative interoperability approaches.

Main Results:

• The DSIA facilitates data exchange across heterogeneous data spaces with minimal independence from specific technologies.
• The architecture demonstrates low governance overheads, simplifying adoption and management.
• Easy deployment is achieved for existing data space participants and authority systems.

Conclusions:

• The proposed Data Space Interoperability Architecture (DSIA) effectively addresses the challenge of cross-data space data exchange.
• DSIA offers a flexible, scalable, and efficient solution for enhancing data space interoperability.
• The architecture's benefits include reduced technological lock-in, streamlined governance, and simplified integration.