The goal of the paper is to analyse the subset of Semantics of Business Vocabulary and Business Rules (SBVR) for a comprehensive representation of ontological knowledge defined using the Web Ontology Language OWL 2. SBVR is the OMG metamodel, which separates the representation and meaning of business concepts and business rules, and makes them understandable for business experts as well as for software systems. The SBVR can act as an interface between business participants and semantic technologies, such as OWL 2 that has developed means for describing ontological data and reasoning with them. SBVR provides the richer model for knowledge representation than OWL 2. Though there are a few proposals that have shown that it is possible to transform the significant subset of SBVR concepts into OWL 2 ontology, the suitability of SBVR to represent OWL 2 ontologies has not been studied in detail. The paper addresses the mentioned issue with regards to the transformation from SBVR into OWL 2.
The fourth industrial evolution, Internet of Things, and large‐scale machine‐to‐machine interactions are driving digital transformation in the industry. Model‐based Systems engineering (MBSE), as a new paradigm of capturing and analyzing knowledge about the system, is one of the core factors to drive this transformation. MBSE practices are more and more widely applied to system‐of‐systems (including enterprise and mission) engineering, which becomes a crucial part of the successful digital transformation. The core challenge today is how digital continuity can be maintained by connecting system models to system‐of‐systems models, especially when multiple parties are involved in their creation and exploration. This paper studies Systems Modeling Language (SysML) as the standard language to model systems, and Unified Architecture Framework (UAF) as the framework and Unified Architecture Framework Profile (UAFP) as the language to model system of systems and proposes an approach for transitioning from one to another in an integrated modeling environment.
Our research is concentrated on defining transformation rules from OWL 2 ontologies into SBVR vocabularies and rules without a loss of information and the expressive power, characteristic for ontologies, overcoming the fact that some ontology-specific concepts have no direct representation in SBVR. Our focus is on generic transformation rules, but the particular attention is devoted to ontologies and vocabularies related with semantic search in Lithuanian Internet corpus. Therefore, we consider some particular constructs related with our application domain, including the idea of creating domain-specific lexical ontologies, related with domain ontologies and capable to support semantic annotating and search.256 Krisciuniene G., Nemuraite L., Butkiene R. and Paradauskas B.. Rules for Transforming OWL 2 Ontology into SBVR.
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