From use case to data space, a bottom-up data space design framework leveraging Data Products.

Area of Science:

• Data Governance
• Information Systems
• Software Engineering

Background:

• Data spaces are critical for secure data sharing in the European Union.
• Practical implementation requires robust design tools for data spaces.
• Existing tools may not fully address the complexities of data space architecture.

Purpose of the Study:

• To propose a novel bottom-up framework for designing data spaces.
• To identify essential data space capabilities for specific use cases.
• To facilitate the practical implementation of data spaces for trusted data sharing.

Main Methods:

• Development of a bottom-up data space design framework.
• Utilizing an intake canvas, inspired by the Open Data Product Specification, to define functional requirements.
• Employing a capability mapping process for data space design.

Main Results:

• The framework was successfully applied to sixteen data space use cases across nine EU countries.
• Valuable insights into data space concepts were gained by stakeholders.
• Limitations of the purely bottom-up approach were identified, highlighting potential gaps in essential capabilities.

Conclusions:

• A combined top-down and bottom-up approach is recommended for comprehensive data space design.
• The proposed framework is domain-agnostic and applicable to various data space initiatives.
• The framework, developed for the deployEMDS project, offers a valuable asset for diverse data space design applications.