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2026
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| Online Access: | https://doi.org/10.5281/zenodo.19653573 |
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| author | Arzani, Radmehr |
| author_facet | Arzani, Radmehr |
| contents | <p>This repository provides the replication materials for the experimental evaluation of SRDF-GEN, a data-driven RDF graph generation framework. It includes all artifacts required to reproduce the comparison with <span class="hover:entity-accent entity-underline inline cursor-pointer align-baseline"><span class="whitespace-normal">RDFGraphGen</span></span> and to validate the reported results.</p> <p>The package contains:</p> <ul> <li><strong>SHACL shapes</strong> derived from Wikidata person entities, used as input for both SRDF-GEN and RDFGraphGen</li> <li><strong>Generated RDF datasets</strong> produced by both systems</li> <li><strong>Configuration details and scripts</strong> used to run the experiments</li> <li><strong>Evaluation outputs</strong>, including predicate distributions and divergence metrics</li> </ul> <p>The SHACL shapes were constructed to model key attributes of person entities (e.g., name, birth date, gender, and address structure) and were used without modification across all experiments to ensure a fair comparison.</p> <p>RDFGraphGen was executed using its official PyPI implementation (https://pypi.org/project/rdf-graph-gen/) with default parameters and a scale factor adjusted to match the order of magnitude of SRDF-GEN outputs. SRDF-GEN was trained on real-world Wikidata instances prior to generation.</p> <p>This replication package is intended to support transparency, reproducibility, and further research on RDF graph generation methods, particularly in comparing constraint-based and data-driven approaches.</p> <p><strong>Keywords:</strong><br>RDF, SHACL, Knowledge Graph Generation, Data Generation, Wikidata, Reproducibility, Graph Data</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19653573 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
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| spellingShingle | Replication Package for "SRDF-GEN: Data-Driven RDF Graph Generation" Arzani, Radmehr <p>This repository provides the replication materials for the experimental evaluation of SRDF-GEN, a data-driven RDF graph generation framework. It includes all artifacts required to reproduce the comparison with <span class="hover:entity-accent entity-underline inline cursor-pointer align-baseline"><span class="whitespace-normal">RDFGraphGen</span></span> and to validate the reported results.</p> <p>The package contains:</p> <ul> <li><strong>SHACL shapes</strong> derived from Wikidata person entities, used as input for both SRDF-GEN and RDFGraphGen</li> <li><strong>Generated RDF datasets</strong> produced by both systems</li> <li><strong>Configuration details and scripts</strong> used to run the experiments</li> <li><strong>Evaluation outputs</strong>, including predicate distributions and divergence metrics</li> </ul> <p>The SHACL shapes were constructed to model key attributes of person entities (e.g., name, birth date, gender, and address structure) and were used without modification across all experiments to ensure a fair comparison.</p> <p>RDFGraphGen was executed using its official PyPI implementation (https://pypi.org/project/rdf-graph-gen/) with default parameters and a scale factor adjusted to match the order of magnitude of SRDF-GEN outputs. SRDF-GEN was trained on real-world Wikidata instances prior to generation.</p> <p>This replication package is intended to support transparency, reproducibility, and further research on RDF graph generation methods, particularly in comparing constraint-based and data-driven approaches.</p> <p><strong>Keywords:</strong><br>RDF, SHACL, Knowledge Graph Generation, Data Generation, Wikidata, Reproducibility, Graph Data</p> |
| title | Replication Package for "SRDF-GEN: Data-Driven RDF Graph Generation" |
| url | https://doi.org/10.5281/zenodo.19653573 |