In progress...
OnSET should enable a more explorative ontology querying experience for non-expert users, and to build a quick understanding of the scale and nature of a KG that is in use.
- Download object and instances form DBPEDIA: DBPEDIA-Data: ontologies, this may take some time!
- Setup a local
qlever
instance (https://github.com/ad-freiburg/qlever-control) (the used configurations can be found indocker/bto-data
anddocker/dbpedia-data
) - Start auxiliary DB using
cd docker/onset-data && docker-compose up -d
- Backend setup:
- install
uv
(https://docs.astral.sh/uv/getting-started/installation/) - install dependencies using
uv sync
- start backend (should initialize DB on first start) using the correct Python installation using
python -m uvicorn api:app --reload --port 8001
- install
- Frontend setup:
- install a somewhat recent Node version
- install dependencies by first
cd frontend && npm i -D
- then start the frontend using
npm run dev
- Profit?
If you feel inspired or want to refer our work in some way, cite the SIGIR Demo Paper:
@misc{kantz2025onsetontologysemanticexploration,
title={OnSET: Ontology and Semantic Exploration Toolkit},
author={Benedikt Kantz and Kevin Innerebner and Peter Waldert and Stefan Lengauer and Elisabeth Lex and Tobias Schreck},
year={2025},
eprint={2504.08373},
archivePrefix={arXiv},
primaryClass={cs.IR},
url={https://arxiv.org/abs/2504.08373},
}