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 goal of the paper is to define requirements to OWL 2 ontologies, under which their semantics may be preserved in a relational database, and to demonstrate that the hybrid approach for transforming OWL 2 ontologies into relational databases possesses such capability. The hybrid approach maps part of ontology concepts to relational database concepts on the base of their common semantics; ontology constructs having no direct equivalents in databases are stored in metatables. The paper defines requirements for ontologies under transformation as ontology normalization and integrity rules, and presents a set of SQL queries for extracting rich data, covering semantics of source ontology, from the resulting database. The capability of the hybrid approach to preserve semantics of OWL 2 ontologies in relational databases is demonstrated with a representative example of a Vehicle ontology.
The goal of the paper is to define reversible, information preserving transformation from OWL 2 ontologies into relational databases using our proposed hybrid approach, when a part of ontology constructs is directly represented by relational database structures and another part having no direct correspondences in a relational database is stored in metadata tables. The desirable transformation is defined in QVT Relations language following additional requirements under which such transformation is reversible and does not lose semantic information when performing from ontology to database and backward.
This paper presents the traceability metamodel for Business Process Model and Notation (BPMN) and its implementation in Cameo Business Modeler plug-in for MagicDraw. There is no public standard traceability metamodel defined for BPMN yet. We present solutions that we have already applied in practice: we improve the traceability of BPMN models by defining derived properties that are calculated by a modeling tool on the fly. In contrast to other existing solutions, this approach does not require additional efforts from users for defining and maintaining traceability, and does not overload projects with redundant information. Using this approach, CASE tool developers are able to supplement their tools with traceability analysis means allowing users to access traceability information easier, to check completeness and correctness of BPMN models, and to analyze the impact of changes.
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