OWL 2 DL ontology merging framework tailored to the production domain
- preprocessing: translations, spell checks, and interactive debugging
- matching: string-similarity-based, terminological, and structural algorithms
- correspondence selection: greedy and optimal regarding the overall similarity score
- postprocessing: link ontology creation and interactive debugging
- quality assessment: calculation of precision, recall, and F-measure
- data/: production vocabulary, helper scripts for downloading ontos, and reference alignments
- docs/: configuration files for various examples, utilities for processing OAEI outputs and reference alignments, graphical abstract
- queries/: queries for information extraction
- src/: sources for creating, loading, preprocessing, matching, and merging the ontologies
- dependency-installer.sh: bash utility for installing dependencies
- cleanup.sh: bash utility for removing temporary and generated files
- Python 3.7
- bash recommended
- on Linux, run the bash script dependency_installer.sh to set up a virtual environment with the packages required
- minimal example: simply run prom.py
- production process example:
- download ontologies and preprocess them using the bash script download_ontos.sh in data/
- adapt the config file, as a reference cp. the file alt_config.yml in docs/
- run prom.py
- for running OAEI benchmarks, cp. the instructions in the utility scripts in docs/
For scientific use, please cite as follows:
@article{ocker2022merging,
title = {A framework for merging ontologies in the context of smart factories},
author = {Ocker, Felix and Vogel-Heuser, Birgit and Paredis, Christiaan JJ},
journal={Computers in Industry},
volume={135},
pages={103571},
year = {2022},
publisher={Elsevier},
doi={10.1016/j.compind.2021.103571}
}
GPL v3.0
Felix Ocker - [email protected]
Technical University of Munich - Institute of Automation and Information Systems