Model driven validation approach for enterprise architecture and motivation extensions

As the endorsement of Enterprise Architecture (EA) modelling continues to grow in diversity and complexity, management of its schema, artefacts, semantics and relationships has become an important business concern. To maintain agility and flexibility within competitive markets, organizations have also been compelled to explore ways of adjusting proactively to innovations, changes and complex events also by use of EA concepts to model business processes and strategies. Thus the need to ensure appropriate validation of EA taxonomies has been considered severally as an essential requirement for these processes in order to exert business motivation; relate information systems to technological infrastructure. However, since many taxonomies deployed today use widespread and disparate modelling methodologies, the possibility to adopt a generic validation approach remains a challenge. The proliferation of EA methodologies and perspectives has also led to intricacies in the formalization and validation of EA constructs as models often times have variant schematic interpretations. Thus, disparate implementations and inconsistent simulation of alignment between business architectures and heterogeneous application systems is common within the EA domain (Jonkers et al., 2003). In this research, the Model Driven Validation Approach (MDVA) is introduced. MDVA allows modelling of EA with validation attributes, formalization of the validation concepts and transformation of model artefacts to ontologies. The transformation simplifies querying based on motivation and constraints. As the extended methodology is grounded on the semiotics of existing tools, validation is executed using ubiquitous query language. The major contributions of this work are the extension of a metamodel of Business Layer of an EAF with Validation Element and the development of EAF model to ontology transformation Approach. With this innovation, domain-driven design and object-oriented analysis concepts are applied to achieve EAF model’s validation using ontology querying methodology. Additionally, the MDVA facilitates the traceability of EA artefacts using ontology graph patterns