Adapting Ontology-based Data Access for Data Spaces

The exponential growth of data across various sectors requires robust frameworks for efficient data management and exchange, particularly in the context of training and improving artificial intelligence (AI) models. Data spaces emerge as a solution, facilitating seamless data exchange among organizations while safeguarding data sovereignty. This article explores the landscape of data spaces, emphasizing the role of Semantic Web standards in achieving interoperability and facilitating data sharing. It begins with use cases in crisis management and manufacturing to provide concrete requirements for discussing data space challenges and benefits. The IDS Data Space Architecture is introduced, alongside an examination of the relevance of Semantic Web standards for data sharing. Examples of searching using Ontology-based Data Access (ODBA) offer insights into the potential of Semantic Web technologies to further improve the interoperability within data spaces. Finally, we explore how to setup a data space and publish data to enable OBDA-based search and the process to conduct the search itself.