Speaking the same language or automated translation? Designing semantic interoperability tools for Data Spaces

Abstract

This paper tackles the challenge of semantic interoperability in the ever-evolving data management and sharing landscape, crucial for integrating diverse data sources in cross-domain use cases. Our comprehensive approach, informed by an extensive literature review, focus-group discussions and expert insights from seven professionals, led to the formulation of six innovative design principles for interoperability tools in Data Spaces. These principles, derived from key meta-requirements identified through semi-structured interviews in a focus group, address the complexities of data heterogeneity and diversity. They offer a blend of automated, scalable, and resilient strategies, bridging theoretical and practical aspects to provide actionable guidelines for semantic interoperability in contemporary data ecosystems. This research marks a significant contribution to the domain, setting a new design approach for Data Space integration and management.