The COBOT use case is concerned with the challenge of low utilization and limited awareness of manufacturing technology in the Aspern pilot factory, which is an Austrian learning and experimentation facility. The factory provides access to a range of industrial machines, including collaborative robots. However, the detailed capabilities of these robots are unknown to potential users due to factors such as limited public availability, contextual dependence, and continuous evolution.
To tackle this issue, we proposed an exploratory search system that allows students, researchers, and companies to explore and learn about the available equipment.
Components of the knowledge graph:
- COBOT ontology
- COBOT data from stakeholder interviews and scraping of public data sources
- STAR1 ontology about software architectural knowledge
- STAR1 data from the central knowledge management system of a software engineering company
Source code of the prototype:
- Middleware: khaller93/es-middleware
- Web application: khaller93/es-web-app
To clone the repository and its submodules, use the following command:
git clone --recursive https://github.com/khaller93/cobot-playground
If you've already cloned the repository and want to load its submodules, use the following commands:
git submodule init
git submodule update
docker-compose up
Then, the web application is available at http://localhost:9080.
docker-compose -f docker-compose.db.yml up
Then, the triplestore is available at http://localhost:7280.
If you make use of this work, please cite the following.
@inproceedings{Haller2022,
author = {Kevin Haller and
Fajar J. Ekaputra and
Marta Sabou and
Florina Piroi},
title = {Enabling Exploratory Search on Manufacturing Knowledge Graphs},
booktitle = {Proceedings of the Seventh International Workshop on the Visualization
and Interaction for Ontologies and Linked Data co-located with the
21st International Semantic Web Conference {(ISWC} 2022), Virtual
Event, Hangzhou, China, October 23, 2022},
series = {{CEUR} Workshop Proceedings},
volume = {3253},
pages = {16--28},
publisher = {CEUR-WS.org},
year = {2022},
url = {http://ceur-ws.org/Vol-3253/paper2.pdf},
}
- Kevin Haller - [email protected]