A Metamodel for Bridging Heterogeneous Ontologies
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ORIGINAL RESEARCH
A Metamodel for Bridging Heterogeneous Ontologies A Fuzzy RDF Approach Luma Oliveira Lombello1 · Rita de Cassia Catini2 · Rodrigo Bonacin3 · Julio Cesar dos Reis4 Received: 23 December 2019 / Accepted: 26 October 2020 © Springer Nature Singapore Pte Ltd 2020
Abstract Soft ontologies aim to provide more flexible knowledge representations as compared with hierarchy-based ontology models. Soft ontologies can restructure itself according to the necessities of an interaction context. This is especially desirable in systems that need to deal with dynamic domains and situations with a high degree of uncertainty. However, the definition of soft ontologies is a challenging task due to the lack of generic and well defined components. In addition, such definition may suffer from problems with interoperability and integration with other models. We argue that soft ontologies should coexist with other models in an interoperable framework. In this paper, we propose and formalize a metamodel to provide adequate conciliation among various ontology representation approaches. We develop soft ontologies based on matrices of probabilities and apply a triplification process in which concepts are represented as fuzzy RDF statements. Our proposal was evaluated in a case study in an educational context, which uses a soft ontology to express a repertoire of actions in an mBot robot. The results indicate the feasibility of our fuzzy RDF approach to represent soft ontologies and the use of the metamodel to support interoperability in heterogeneous ontology networks. Keywords Ontology · Soft ontologies · Fuzzy · RDF · Triples · Linked data
Introduction The web and mobile systems are increasingly present in people’s daily tasks. The domain associated with these tasks is often inaccurate as well as it includes poorly defined This article is part of the topical collection “Web for Information and Knowledge Exploration, Sharing and Security (Section 1: Web2Touch)” guest edited by Haider Abbas, Hammad Afzal, Rodrigo Bonacin, Ismail Bouassida, Khalil Drira, Riccardo Martoglia, Olga Nabuco and Fatiha Saïs. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s42979-020-00386-7) contains supplementary material, which is available to authorized users.
concepts and subjective interpretations. The categorization of data stored and used in these systems is essential to improve new interactive systems. The shared content must be interpretable by both machines and humans. Ontologies are used to represent objects, their relationships and provide definitions that are necessary for this mutual interpretation [6]. In Computer Science, ontologies are modeled to represent knowledge and provide advanced software applications in various fields such as artificial intelligence, databases, natural language processing, software engineering, and Semantic Web [34]. The Ontology Web Language (OWL) and Resource
* Julio Cesar dos Reis [email protected]
1
Institute of Computing, University of Campin
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