Record link: 
http://hdl.handle.net/20.500.12708/227282
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Title: 
RDFGraphGen: An RDF Graph Generator Based on SHACL Shapes
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Citation: 
Jovanovik, M., Vecovska, M., Jakubowski, M., & Hose, K. (2026). RDFGraphGen: An RDF Graph Generator Based on SHACL Shapes. In Knowledge Graphs : 14th International Joint Conference, IJCKG 2025, Heraklion, Crete, Greece, October 15–17, 2025, Proceedings (pp. 111–125). Springer. https://doi.org/10.1007/978-981-95-5009-8_8
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Publisher DOI: 
10.1007/978-981-95-5009-8_8
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Jovanovik, Milos 
Vecovska, Marija 
Jakubowski, Maxime 
Hose, Katja 
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Organisational Unit: 
E192-02 - Forschungsbereich Databases and Artificial Intelligence 
E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML) 
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Published in: 
Knowledge Graphs : 14th International Joint Conference, IJCKG 2025, Heraklion, Crete, Greece, October 15–17, 2025, Proceedings 
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ISBN: 
978-981-95-5009-8
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Volume: 
16297
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DOI of the book: 
10.1007/978-981-95-5009-8
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Date (published): 
1-Apr-2026
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Event name: 
14th International Joint Conference on Knowledge Graphs (IJCGK 2025) 
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Event date: 
15-Oct-2025 - 17-Oct-2025
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Event place: 
Heraklion, Crete, Greece
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Number of Pages: 
15
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Publisher: 
Springer, Singapore
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Peer reviewed: 
Yes
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Keywords: 
Data Generator; Synthetic Data; Knowledge Graphs; RDF; SHACL
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Abstract: 
Developing and testing modern RDF-based applications often requires access to RDF datasets with certain characteristics. Unfortunately, it is very difficult to publicly find domain-specific knowledge graphs that conform to a particular set of characteristics. Hence, in this paper we propose RDFGraphGen, an open-source RDF graph generator that uses characteristics provided in the form of SHACL (Shapes Constraint Language) shapes to generate synthetic RDF graphs. RDFGraphGen is domain-agnostic, with configurable graph structure, value constraints, and distributions. It also comes with a number of predefined values for popular schema.org classes and properties, for more realistic graphs. Our results show that RDFGraphGen is scalable and can generate small, medium, and large RDF graphs in any domain.
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Project title: 
Health virtual twins for the personalised management of stroke related to atrial fibrillation: 101136244 (European Commission) 
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Project (external): 
Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, N. Macedonia
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Link (external): 
https://github.com/etnc/RDFGraphGen
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Research Areas: 
Logic and Computation: 80%
Information Systems Engineering: 20%
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Science Branch: 
1020 - Informatik: 80%
1010 - Mathematik: 20%
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Appears in Collections:
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