Towards a Toolkit for Semantic Interoperability in Data Spaces

Achieving semantic interoperability in data spaces is essential for enabling secure, efficient, and scalable data exchange across industries. While data spaces facilitate collaboration by connecting heterogeneous datasets, significant challenges persist in aligning and harmonizing data from diverse stakeholders. This paper introduces a toolkit designed to enhance semantic interoperability through ontology management, entity linking, and data transformation. Central to this toolkit is the Ontology Library, which serves as the Vocabulary Hub of the Data Space Reference Architecture Model (RAM), providing standardized vocabularies and facilitating consistent data interpretation. In addition to the Ontology Library, data harmonization tools automate entity linking, data enrichment and representation processes. By leveraging advanced Machine Learning approaches, the toolkit reduces manual effort and improves the accuracy of data integration. This work contributes to the development of scalable and adaptable solutions, fostering seamless data exchange within industrial ecosystems and advancing the adoption of data spaces in circular manufacturing and beyond.