Web Interoperability for Ontology Development and Support with crowd 2.0
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Demo Track. Pages 4980-4983.
https://doi.org/10.24963/ijcai.2021/707
Keywords
- Knowledge Representation and Reasoning: General
Abstract
In this work, we treat web interoperability in terms of interchanging ontologies (as knowledge models) within user-centred ontology engineering environments, involving visual and serialised representations of ontologies.
To do this, we deal with the tool interoperability problem by re-using an enough expressive ontology-driven metamodel, named KF, proposed as a bridge for interchanging both knowledge models.
We provide an extensible web framework, named crowd 2.0, unifying the standard conceptual data modelling languages for generating OWL 2 ontologies from semantic visualisations. Visual models are designed as UML, ER or ORM 2 diagrams, represented as KF instances, and finally, formalised as DL-based models. Reasoning results may be newly incorporated into the shared KF instance to be visualised in any of the provided languages.
@inproceedings{ijcai2021p707,
title = {Web Interoperability for Ontology Development and Support with crowd 2.0},
author = {Braun, German and Marinelli, Giuliano and Rios Gavagnin, Emiliano and Cecchi, Laura and Fillottrani, Pablo},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Prof. Zhi-Hua Zhou},
pages = {4980--4983},
year = {2021},
month = {8},
note = {Demo Track},
doi = {10.24963/ijcai.2021/707},
url = {https://doi.org/10.24963/ijcai.2021/707},
}
TY - CPAPER TI - Web Interoperability for Ontology Development and Support with crowd 2.0 AU - Braun, German AU - Marinelli, Giuliano AU - Rios Gavagnin, Emiliano AU - Cecchi, Laura AU - Fillottrani, Pablo T2 - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2021 SP - 4980 EP - 4983 DO - 10.24963/ijcai.2021/707 UR - https://doi.org/10.24963/ijcai.2021/707 ER -Copied
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