<div class="csl-bib-body">
<div class="csl-entry">Jovanovik, M., Vecovska, M., Jakubowski, M., & Hose, K. (2026). RDFGraphGen: An RDF Graph Generator Based on SHACL Shapes. In <i>Knowledge Graphs : 14th International Joint Conference, IJCKG 2025, Heraklion, Crete, Greece, October 15–17, 2025, Proceedings</i> (pp. 111–125). Springer. https://doi.org/10.1007/978-981-95-5009-8_8</div>
</div>
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/227282
-
dc.description.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.
en
dc.description.sponsorship
European Commission
-
dc.language.iso
en
-
dc.relation.ispartofseries
Lecture Notes in Computer Science
-
dc.subject
Data Generator
en
dc.subject
Synthetic Data
en
dc.subject
Knowledge Graphs
en
dc.subject
RDF
en
dc.subject
SHACL
en
dc.title
RDFGraphGen: An RDF Graph Generator Based on SHACL Shapes
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.relation.isbn
978-981-95-5009-8
-
dc.relation.doi
10.1007/978-981-95-5009-8
-
dc.relation.issn
0302-9743
-
dc.description.startpage
111
-
dc.description.endpage
125
-
dc.relation.grantno
101136244
-
dc.type.category
Full-Paper Contribution
-
dc.relation.eissn
1611-3349
-
tuw.booktitle
Knowledge Graphs : 14th International Joint Conference, IJCKG 2025, Heraklion, Crete, Greece, October 15–17, 2025, Proceedings
-
tuw.container.volume
16297
-
tuw.peerreviewed
true
-
tuw.book.ispartofseries
Lecture Notes in Computer Science
-
tuw.relation.publisher
Springer
-
tuw.relation.publisherplace
Singapore
-
tuw.project.title
Health virtual twins for the personalised management of stroke related to atrial fibrillation
-
tuw.researchTopic.id
I1
-
tuw.researchTopic.id
I4
-
tuw.researchTopic.name
Logic and Computation
-
tuw.researchTopic.name
Information Systems Engineering
-
tuw.researchTopic.value
80
-
tuw.researchTopic.value
20
-
tuw.linking
https://github.com/etnc/RDFGraphGen
-
tuw.publication.orgunit
E192-02 - Forschungsbereich Databases and Artificial Intelligence
-
tuw.publication.orgunit
E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML)
-
tuw.publisher.doi
10.1007/978-981-95-5009-8_8
-
dc.description.numberOfPages
15
-
tuw.author.orcid
0000-0001-7360-8015
-
tuw.author.orcid
0000-0002-7420-1337
-
tuw.author.orcid
0000-0001-7025-8099
-
tuw.event.name
14th International Joint Conference on Knowledge Graphs (IJCGK 2025)
en
dc.description.sponsorshipexternal
Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, N. Macedonia
-
tuw.event.startdate
15-10-2025
-
tuw.event.enddate
17-10-2025
-
tuw.event.online
On Site
-
tuw.event.type
Event for scientific audience
-
tuw.event.place
Heraklion, Crete
-
tuw.event.country
GR
-
tuw.event.presenter
Jakubowski, Maxime
-
wb.sciencebranch
Informatik
-
wb.sciencebranch
Mathematik
-
wb.sciencebranch.oefos
1020
-
wb.sciencebranch.oefos
1010
-
wb.sciencebranch.value
80
-
wb.sciencebranch.value
20
-
item.cerifentitytype
Publications
-
item.fulltext
no Fulltext
-
item.openairecristype
http://purl.org/coar/resource_type/c_5794
-
item.grantfulltext
none
-
item.openairetype
conference paper
-
item.languageiso639-1
en
-
crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
-
crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
-
crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
