{"citation":{"apa":"Halimeh, H., &#38; zur Heiden, P. (2025). Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces. <i>2025 27th International Conference on Business Informatics (CBI)</i>. <a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">https://doi.org/10.1109/cbi68102.2025.00019</a>","chicago":"Halimeh, Haya, and Philipp zur Heiden. “Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces.” In <i>2025 27th International Conference on Business Informatics (CBI)</i>. IEEE, 2025. <a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">https://doi.org/10.1109/cbi68102.2025.00019</a>.","short":"H. Halimeh, P. zur Heiden, in: 2025 27th International Conference on Business Informatics (CBI), IEEE, 2025.","ama":"Halimeh H, zur Heiden P. Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces. In: <i>2025 27th International Conference on Business Informatics (CBI)</i>. IEEE; 2025. doi:<a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">10.1109/cbi68102.2025.00019</a>","bibtex":"@inproceedings{Halimeh_zur Heiden_2025, title={Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces}, DOI={<a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">10.1109/cbi68102.2025.00019</a>}, booktitle={2025 27th International Conference on Business Informatics (CBI)}, publisher={IEEE}, author={Halimeh, Haya and zur Heiden, Philipp}, year={2025} }","ieee":"H. Halimeh and P. zur Heiden, “Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces,” 2025, doi: <a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">10.1109/cbi68102.2025.00019</a>.","mla":"Halimeh, Haya, and Philipp zur Heiden. “Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces.” <i>2025 27th International Conference on Business Informatics (CBI)</i>, IEEE, 2025, doi:<a href=\"https://doi.org/10.1109/cbi68102.2025.00019\">10.1109/cbi68102.2025.00019</a>."},"title":"Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces","_id":"63523","year":"2025","main_file_link":[{"open_access":"1"}],"user_id":"87673","publisher":"IEEE","publication":"2025 27th International Conference on Business Informatics (CBI)","department":[{"_id":"195"},{"_id":"196"}],"oa":"1","author":[{"first_name":"Haya","id":"87673","full_name":"Halimeh, Haya","last_name":"Halimeh"},{"id":"64394","first_name":"Philipp","full_name":"zur Heiden, Philipp","last_name":"zur Heiden"}],"status":"public","language":[{"iso":"eng"}],"abstract":[{"text":"Data spaces have become a strategic pillar of Europe's digital agenda, enabling sovereign, legally compliant data sharing within decentralized ecosystems. As data space initiatives evolve, personalized recommendations are increasingly recognized as key use cases. However, traditional recommendation approaches typically rely on centralized aggregation of user behavior data-directly conflicting with the core ethos of data spaces: sovereignty, privacy, and trust. Federated recommendation systems offer a promising alternative by training models locally and exchanging only intermediate parameters to build a global model. Despite this potential, the integration of federated recommendation techniques and data space architectures remains largely underexplored in research and practice. This paper addresses this gap by designing and evaluating a prototype of a federated recommendation system specifically tailored for data spaces and compliant with their underlying infrastructure. Our findings highlight the viability of developing privacy-preserving, collaborative recommendation systems within data spaces, and contribute to the broader adoption of AI across these emerging ecosystems.","lang":"eng"}],"doi":"10.1109/cbi68102.2025.00019","publication_status":"published","date_updated":"2026-01-07T13:49:45Z","date_created":"2026-01-07T13:34:02Z","type":"conference"}