Transforming enterprise ontologies into SBVR formalizations

In 2007 the Object Management Group (OMG) adopted the Se- mantics of Business Vocabulary and Business Rules (SBVR) specification. The languages specified by this specification must be used to create business vocab- ularies and business rules of all kinds of business activities of all kinds of or- ganizations. This paper describes and demonstrates how enterprise ontologies can be transformed into SBVR formalizations

The Structured Process Modeling Method (SPMM) : what is the best way for me to construct a process model?

More and more organizations turn to the construction of process models to support strategical and operational tasks. At the same time, reports indicate quality issues for a considerable part of these models, caused by modeling errors. Therefore, the research described in this paper investigates the development of a practical method to determine and train an optimal process modeling strategy that aims to decrease the number of cognitive errors made during modeling. Such cognitive errors originate in inadequate cognitive processing caused by the inherent complexity of constructing process models. The method helps modelers to derive their personal cognitive profile and the related optimal cognitive strategy that minimizes these cognitive failures. The contribution of the research consists of the conceptual method and an automated modeling strategy selection and training instrument. These two artefacts are positively evaluated by a laboratory experiment covering multiple modeling sessions and involving a total of 149 master students at Ghent University

The Structured Process Modeling Theory (SPMT): a cognitive view on why and how modelers benefit from structuring the process of process modeling

After observing various inexperienced modelers constructing a business process model based on the same textual case description, it was noted that great differences existed in the quality of the produced models. The impression arose that certain quality issues originated from cognitive failures during the modeling process. Therefore, we developed an explanatory theory that describes the cognitive mechanisms that affect effectiveness and efficiency of process model construction: the Structured Process Modeling Theory (SPMT). This theory states that modeling accuracy and speed are higher when the modeler adopts an (i) individually fitting (ii) structured (iii) serialized process modeling approach. The SPMT is evaluated against six theory quality criteria

Developing an ontological sandbox : investigating multi-level modelling’s possible Metaphysical Structures

One of the central concerns of the multi-level modelling (MLM) community is the hierarchy of classifications that appear in conceptual models; what these are, how they are linked and how they should be organised into levels and modelled. Though there has been significant work done in this area, we believe that it could be enhanced by introducing a systematic way to investigate the ontological nature and requirements that underlie the frameworks and tools proposed by the community to support MLM (such as Orthogonal Classification Architecture and Melanee). In this paper, we introduce a key component for the investigation and understanding of the ontological requirements, an ontological sandbox. This is a conceptual framework for investigating and comparing multiple variations of possible ontologies – without having to commit to any of them – isolated from a full commitment to any foundational ontology. We discuss the sandbox framework as well as walking through an example of how it can be used to investigate a simple ontology. The example, despite its simplicity, illustrates how the constructional approach can help to expose and explain the metaphysical structures used in ontologies, and so reveal the underlying nature of MLM levelling

Comprehending 3D and 4D ontology-driven conceptual models: An empirical study

This paper presents an empirical study that investigates the extent to which the pragmatic quality of ontology-driven models is influenced by the choice of a particular ontology, given a certain understanding of that ontology. To this end, we analyzed previous research efforts and distilled three hypotheses based on different metaphysical characteristics. An experiment based on two foundational ontologies (UFO and BORO) involving 158 participants was then carried out, followed by a protocol analysis to gain further insights into the results of experiment. We then extracted five derivations from the results of the empirical study in order to summarize our findings. Overall, the results confirm that the choice of a foundational ontology can lead to significant differences in the interpretation and comprehension of the conceptual models produced. Moreover, the effect of applying a certain foundational ontology can cause considerable variations in the effort required to comprehend these models

Enterprise-specific ontology-driven process modelling

Different process models are created within an enterprise by different modelers who use different enterprise terms. This hinders model interoperability and integration. A possible solution is formalizing the vocabulary used within the enterprise in an ontology and put this ontology as bases for constructing process models. Given that an enterprise is an evolving entity, the ontology needs to evolve to properly reflect the domain of the enterprise. This paper proposes an enterprise-specific ontology-driven process modelling method which tackles the two aforementioned issues by assisting the modeller in creating process models using terminology from the ontology and simultaneously supporting ontology enrichment with feedback from those models. When the modeller creates a model, matching mechanisms incorporated in the method are working together to suggest a list of ontological concepts that have a high potential to be useful for a particular modelling element. When the model is created, its quality is first evaluated from different perspectives to make sure that it can be used within the enterprise, and second to discover whether its feedback can be useful for the ontology. When the feedback is extracted, the proposed method incorporates guidelines on how to use this feedback

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Modeling loosely framed and knowledge-intensive business processes with the currently available process modeling languages is very challenging. Some lack the flexibility to model this type of processes, while others are missing one or more-perspectives needed to add the necessary level of detail to the models. In this paper we have composed a list of requirements that a modeling language should fulfil in order to adequately support the modeling of this type of processes. Based on these requirements, a metamodel for a new modeling language was developed that satisfies them all. The new language, called DeciClare, incorporates parts of several existing modeling languages, integrating them with new solutions to requirements that had not yet been met, Deciclare is a declarative modeling language at its core, and therefore, can inherently deal with the flexibility required to model loosely framed processes. The complementary resource and data perspectives add the capability to reason about, respectively, resources and data values. The latter makes it possible to encapsulate the knowledge that governs the process flow by offering support for decision modeling. The abstract syntax of DeciClare has been implemented in the form of an Ecore model. Based on this implementation, the language-domain appropriateness of the language was validated by domain experts using the arm fracture case as application scenario. (C) 2017 Elsevier Ltd. All rights reserved

A toolkit for business process owners to capture early system requirements

Semantic Business Process Management (SBPM) raises Business Process Management (BPM) from the IT level, where it mostly resides now, to the business level, where it belongs. SBPM provides a rich ontological description of both enterprise and process aspects, and aims to support business process modellers by means of SBPM modelling tools. Unfortunately, no explicit support is foreseen to capture early system requirements coming from the business process owner. To meet this need, we propose a toolkit approach and provide a mapping algorithm to semi-automatically insert the acquired business knowledge in the SBPM modelling environment