# TransformingBPMN Processes toSBVR Process Rules with
## 2 Related Work  
### State of the Art Research  
Neither the integration of business processes with business rules nor the representation of business processes in natural language text (and vice versa) are novel ideas whatsoever. In model-driven ISD, the idea of integrating the two very much related aspects of business knowledge has been around for three decades, counting from the first notable publication on this subject in 1991 [10]. Since then, numerous pieces of research have been conducted, providing a variety of integration approaches and applications [11; 12; 13; 14; 15; 16; 17; 18]. At the same time, the representation of graphical business processes in natural language text has also gained significant attention. Most recently, [PERSON] et al., presented their approach for the user-assisted visual annotation of business process-related elements in textual documents [19]. The process model to text transformations (M2T) have gained ground in requirements engineering as well, e.g., [PERSON] et al., generated well-structured system requirements documents from visual process models [20]. Meanwhile, others researched transformations in the opposite direction, that is, extracting process models from various textual documents [21; 22; 23; 24]. In most of the overviewed related work, we observed one common issue with natural language texts, which is the inherent ambiguity and the lack of proper structuring of business knowledge expressed in natural language. In [25], the authors conclude that even the most advanced natural language processing (NLP) techniques still face many challenges when dealing with natural language texts in the domain of BPM; obviously, the same situation is inherent in the domain of ISD as well. In other words, without proper formalization, the representation of business knowledge in natural language presents a considerable challenge to the practical application of that business knowledge in BPM, ISD, and, presumably, other relevant domains. We argue that OMG's Semantics of Business Vocabulary and Business Rules [8] provides all the required means to properly structure and formalize business knowledge while at the same time retaining the positive aspects provided by the natural language representation. In one of his interviews, [PERSON], who is a renowned person in the business rules community, said that \"SBVR is an extremely powerful method to formalize knowledge, forming a solid base for contracts, end-user documentation, work instructions, process design, and product development\" [26]. Some go even further by stating that SBVR coupled with BPMN provides an optimal combination for expressing the semantics of business knowledge [27; 28]. Moreover, SBVR specifications can be transformed into various conceptual modeling as well as software artifacts [29; 30; 31; 32]. While there are many approaches researched on the integration of business processes and business rules, there is not much research on integrating specifically the concepts of BPMN and SBVR [33; 34; 35] and even less so on transforming BPMN processes to natural language-based SBVR business vocabularies and rules. Other than our own findings [36; 37], the results of just a few other research pieces are to be found on the internet. In [36], we presented the SBVR and BPMN standards-based approach for the extraction of SBVR business vocabularies from BPMN process models; notably, only the business vocabulary part of the SBVR specification was considered in that research. In [37], certain founding principles for extracting SBVR process rules from the process models together with the experimentation results were presented; this research item lies in the fundament of the research work presented in this paper. Other than [37], only two other papers [38; 39] published by the same authors presented some early research results describing the representation of BPMN processes in a form of SBVR process rules.