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Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips
| Date | Stars |
|---|---|
| 2026-07-24 | 710 |
| 2026-07-25 | 710 |
| 2026-07-28 | 710 |
| 2026-07-30 | 710 |
| 2026-07-31 | 713 |
| 2026-08-06 | 713 |
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# [PyGraft: Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips](https://arxiv.org/pdf/2309.03685.pdf)
This is the open-source implementation of PyGraft, initially presented in [this paper](https://arxiv.org/pdf/2309.03685.pdf).
PyGraft is an open-source Python library for generating synthetic yet realistic schemas and (KGs) based on user-specified parameters. The generated resources are domain-agnostic, i.e. they are not tied to a specific application field.
Being able to synthesize schemas and KGs is an important milestone for conducting research in domains where data is sensitive or not readily available. PyGraft allows researchers and practitioners to generate schemas and KGs on the fly, provided minimal knowledge about the desired specifications.
PyGraft has the following features:
- possibility to generate a schema, a KG, or both
- highly-tunable process based on a broad array of user-specified parameters
- schemas and KGs are built with an extended set of RDFS and OWL constructs
- logical consistency is ensured by the use of a DL reasoner (HermiT)
## Installation
The latest stable version of PyGraft can be downloaded and installed from [PyPI](https://pypi.org/project/pygraft) with:
```bash
pip install pygraft
```
The latest version of PyGraft can be installed directly from [GitHub](https://github.com/nicolas-hbt/pygraft) source with:
```bash
pip install git+https://github.com/nicolas-hbt/pygraft.git
```
## Upcoming Features
Additional features will be provided in the next versions of PyGraft. To name but a few:
**High Priority**
- [ ] Allow support for any input schema (and not only the schemas generated by PyGraft).
- [ ] Allow explanations for inconsistencies to be parsed from HermiT API. This would make it possible to remove a subset of triples from inconsistent KGs to make them consistent, without needing the user to run the KG generation pipeline again. This is especially true for very large graphs, or if the user comes with an already existing schema which is not perfectly consistent.
**Medium Priority**
- [ ] Fix the conflict between the following properties ``rdfs:subPropertyOf``, ``owl:FunctionalProperty``, and ``owl:InverseFunctionalProperty``, as a non-zero value for the three of them at the same time can lead to inconsistent KGs.
**Low Priority**
- [ ] Facilitate the generation of larger KGs (this would imply removing any dependency to [rdflib](https://github.com/RDFLib/rdflib/)).
- [ ] Add support for literals.
## PyGraft Overview
The contributions of PyGraft are as follows:
- To the best of our knowledge, PyGraft is the first generator able to synthesize both schemas and KGs in a single pipeline.
- The generated schemas and KGs are described with an extended set of RDFS and OWL constructs, allowing for both fine-grained resource descriptions and strict compliance with common Semantic Web standards.
- A broad range of parameters can be specified by the user. These allow for creating an infinite number of graphs with different characteristics. More details on parameters can be foundExcerpt of 8,841 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:3adc4061387dddd9, topic:synthetic-data
matched fp:3adc4061387dddd9, topic:knowledge-graph