An Agile and Ontology-Aided Approach for Domain-Specific Adaptations of Modelling Languages

Abstract

Domain-Specific Modelling Languages (DSMLs) offer constructs that are tailored to better capture the representational needs of an application domain. They provide customized graphical notations, which facilitate understanding of models by domain experts. As a result, DSMLs allow the construction of domain-specific models that support collaboration, improve work processes and enhance decision-making. Given their special purpose, however, a DSML has to be built each time a new application domain is to be addressed, which is quite demanding and time-consuming. A valid alternative is the creation of DSMLs through domain-specific adaptations of existing modelling languages. This solution has the benefits of starting from a baseline of well-known concepts, which is adapted to fit a specific purpose. Current engineering processes for building or adapting modelling languages, however, lack agility. It follows a sequential engineering lifecycle, where modelling and evaluation activities cannot start before the DSML is deployed for use. Such a sequential approach tends to keep the language engineer separate from the domain expert, who is hindered from gaining experience from the DSML until it is created. The separation of the two roles is a threat to the high quality of the DSML as it requires the joint effort of both experts. On the other hand, the new requirements that arise from the suggestions of the domain expert have to go through the whole engineering lifecycle (i.e. capture and document the requirement, conceptualise, implement and deploy), which is time-consuming. These current drawbacks of present engineering processes have been explored in two case studies, which report the development of a DSML for Patient Transferal Management and a DSML for Business Process as a Service. In this research an agile meta-modelling approach has been conceived to address the identified drawbacks. Specifically, the approach allows the quick interleaving of language engineering, modelling and evaluation activities. Hence, the close cooperation between the language engineers and the domain experts is fostered from an early stage. A set of operators are proposed to enable on-the-fly domain-specific adaptations of modelling languages, thus avoiding the sequential engineering phases. This agile meta-modelling aims to promote both the high-quality and quick development of DSMLs through domain-specific adaptations. Moreover, to avoid misinterpretation of the meaning of the newly created modelling constructs as well as ensuring machine interpretability of models, the agile meta-modelling has been supplemented by an ontology-aided approach. The latter embeds the specification specifications of modelling languages into an ontology. A set of semantic rules are proposed to support the propagation of language adaptations from the graphical to the machine-interpretable representation. In turn, the approach was developed in the modelling environment AOAME, which allows preserving consistency between the graphical and the machine-interpretable knowledge while domain-specific adaptations are performed. An evaluation strategy is proposed, from which three criteria were derived to evaluate the approach. Firstly, the correct design of the approach is evaluated by the extent to which it satisfies the requirements. Secondly, the operationability of the approach is evaluated by its ability to preserve consistency between the graphical and the machine-interpretable representations. Thirdly, the generality of the approach is evaluated by its ability to be applied in different application domains. The evaluation of operationability and generality are supported by implementing real-world use cases in AOAME. Consequently, the approach contributes to the practice in three different application domains, the Patient Transferal Management, Business Process as a Service and Innovation Processes. The scientific contribution of the approach spans research fields of Domain-Specific Modelling Language, Meta-Modelling, Enterprise Modelling and Ontologies.