Authors:
Maximilian Stäbler
1
;
Tobias Guggenberger
2
;
DanDan Wang
3
;
Richard Mrasek
4
;
Frank Köster
1
and
Chris Langdon
5
Affiliations:
1
German Aerospace Center (DLR), Institute for AI Safety and Security, Ulm, Germany
;
2
Fraunhofer ISST, Dortmund, Germany
;
3
T-Systems International GmbH, Bonn, Germany
;
4
T-Systems International GmbH, Darmstadt, Germany
;
5
Drucker School of Business, Claremont Graduate University, Claremont, U.S.A.
Keyword(s):
Data Spaces, Semantic Interoperability, Design Principles, Data Ecosystem.
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.