Record link: 
http://hdl.handle.net/20.500.12708/231486
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Title: 
Scalable and Privacy-Aware Relational Data Synthesis
en
Citation: 
Kapenekakis, A., Dell’Aglio, D., Bøgsted, M., Garofalakis, M., & Hose, K. (2026). Scalable and Privacy-Aware Relational Data Synthesis. In G. DEJAEGERE, A. Abelló, K. Torp, & A. Simitsis (Eds.), Data Engineering for Data Science (pp. 63–77). Springer Cham. https://doi.org/10.1007/978-3-032-18765-9_3
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Publisher DOI: 
10.1007/978-3-032-18765-9_3
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Publication Type: 
Book Contribution - Edited Volume Contribution
en
Language: 
English
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Authors: 
Kapenekakis, Antheas 
Dell'Aglio, Daniele 
Bøgsted, Martin 
Garofalakis, Minos 
Hose, Katja 
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Organisational Unit: 
E194-07 - Forschungsbereich Data Management 
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Published in: 
Data Engineering for Data Science 
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ISBN: 
978-3-032-18764-2
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DOI of the book: 
10.1007/978-3-032-18765-9
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Date (published): 
30-May-2026
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Number of Pages: 
15
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Publisher: 
Springer Cham
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Peer reviewed: 
Yes
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Keywords: 
Data Synthesis; Privacy; Sensitive Data
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Research Areas: 
Logic and Computation: 20%
Information Systems Engineering: 80%
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Science Branch: 
1020 - Informatik: 100%
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Appears in Collections:
Book Contribution

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