Search Results (4)

Semantics of Business Vocabulary and Rules (SBVR) is a standard that is applied in describing business knowledge in the form of controlled natural language. Business process designers develop SBVR from formal documents and later translate it into business process models. In many immature companies, these documents are often unavailable and could hinder resource efficiency efforts. This study introduced a novel approach called informal document to SBVR (ID2SBVR). This approach is used to extract operational rules of SBVR from informal documents. ID2SBVR mines fact type candidates using word patterns or extracting triplets (actor, action, and object) from sentences. A candidate fact type can be a complex, compound, or complex-compound sentence. ID2SBVR extracts fact types from candidate fact types and transforms them into a set of SBVR operational rules. The experimental results show that our approach can be used to generate the operational rules of SBVR from informal documents with an accuracy of 0.91. Moreover, ID2SBVR can also be used to extract fact types with an accuracy of 0.96. The unstructured data is successfully converted into semi-structured data for use in pre-processing. ID2SBVR allows the designer to automatically generate business process models from informal documents. Full article

The Object Management Group (OMG) has put considerable effort into the standardization of various business modeling aspects within the context of model-driven systems development. Indeed, the Business Process Model and Notation (BPMN) is now arguably the most popular process modeling language. At the same time, the Semantics of Business Vocabulary and Business Rules (SBVR), which is a novel and formally sound standard for the specification of virtually any kind of knowledge using controlled natural language, is also gaining its grounds. Nonetheless, the integration between these two very much related standards remains weak. In this paper, we present one such integration effort, namely an approach for the extraction of SBVR process rules from BPMN processes. To accomplish this, we utilized model-to-model transformation technology, which is one of the core features of Model-Driven Architecture. At the core of the presented solution stands a set of model transformation rules and two algorithms specifying the formation of formally defined process rules from process models. Basic implementation aspects, together with the source code of the solution, are also presented in the paper. The experimental results acquired from the automatic model transformation have shown full compliance with the benchmark results and cover the entirety of the specified flow of work defined in the experimental process models. Following this, it is safe to conclude that the set of specified transformation rules and algorithms was sufficient for the given scope of the experiment, providing a solid background for the practical application and future developments of the solution. Full article

In the domain of model-driven system engineering, model-to-model (M2M) transformations present a very relevant topic because they may provide much-needed automation capabilities to the whole CASE-supported system development life cycle. Nonetheless, it is observed that throughout the whole development process M2M transformations are spread unevenly; in this respect, the phases of Business Modeling and System Analysis are arguably the most underdeveloped ones. The main novelty and contributions of this paper are the presented set of model-based transformations for extracting well-structured SBVR business vocabularies from visual UML use case models, which utilizes M2M transformation technology based on the so-called drag-and-drop actions. The conducted experiments show that this new development provides the same transformation power while introducing more flexibility to the model development process as compared to our previously developed approach for (semi-)automatic extraction of SBVR business vocabularies from UML use case models. Full article

Regulations in the Building Industry are becoming increasingly complex and involve more than one technical area, covering products, components and project implementations. They also play an important role in ensuring the quality of a building, and to minimize its environmental impact. Control or conformance checking are becoming more complex every day, not only for industrials, but also for organizations charged with assessing the conformity of new products or processes. This paper will detail the approach taken by the CSTB (Centre Scientifique et Technique du Bâtiment) in order to simplify this conformance control task. The approach and the proposed solutions are based on semantic web technologies. For this purpose, we first establish a domain-ontology, which defines the main concepts involved and the relationships, including one based on OWL (Web Ontology Language) [1]. We rely on SBVR (Semantics of Business Vocabulary and Business Rules) [2] and SPARQL (SPARQL Protocol and RDF Query Language) [3] to reformulate the regulatory requirements written in natural language, respectively, in a controlled and formal language. We then structure our control process based on expert practices. Each elementary control step is defined as a SPARQL query and assembled into complex control processes “on demand”, according to the component tested and its semantic definition. Finally, we represent in RDF (Resource Description Framework) [4] the association between the SBVR rules and SPARQL queries representing the same regulatory constraints. Full article