Production Ontology Merging (PrOM) Framework
OWL 2 DL ontology merging framework tailored to the production domain
Features
- 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
Contents
- 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
Requirements
- Python 3.7
- bash recommended
Instructions
- on Linux, run the bash script dependency_installer.sh to set up a virtual environment with the packages required
- minimal example: simply run main.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 main.py
- for running OAEI benchmarks, cp. the instructions in the utility scripts in docs/
Citation
For scientific use, please cite using the following bibtex entry:
@article{ocker2021cii,
title = {{A Framework for Merging Ontologies in the Context of Smart Factories (accepted)}},
author = {Ocker, Felix and Vogel-Heuser, Birgit and Paredis, Christiaan JJ},
journal={Computers in Industry},
year = {2021},
publisher={Elsevier}
}
License
GPL v3.0
Contact
Felix Ocker - [email protected]
Technical University of Munich - Institute of Automation and Information Systems