Automatic Ontology-based Validation of Enterprise Architecture Principles

Enterprise Architecture (EA) principles serve as foundational guidelines governing the design, implementation, and evolution of enterprise systems. However, their valida- tion poses significant challenges due to their articulation in natural language, which often lacks the precision needed for automated processes. EA models, predominantly represented graphically, require human interpretation to ensure alignment with these principles. This research addresses these challenges by introducing an ontology-based validation approach, leveraging semantic technologies to formalize and partially auto- mate the validation of EA principles. The study follows the Design Science Research (DSR) methodology, which provides a rigorous framework for developing and evaluating practical solutions. Through iterative cycles of design, implementation, and validation, the research refines the approach to ensure both methodological rigor and practical relevance. At the core of this approach lies the ArchiMEO ontology, a formal semantic representa- tion tailored to capturing EA concepts and their relationships. By transforming natural language principles into machine-interpretable rules and mapping them to EA mod- els using ArchiMEO, the approach enables automated reasoning and validation. The structured representation of principles and models facilitates accurate assessments of compliance and reduces reliance on manual intervention. The methodology was evaluated through three comprehensive case studies in real-world enterprise settings. These case studies demonstrated the translation of existing EA mod- els and principles into the ArchiMEO ontology, followed by the application of automated validation techniques. The results confirm the scalability and applicability of the ap- proach, highlighting its effectiveness in ensuring adherence to EA principles, enhancing decision-making, and improving enterprise governance. This research contributes to the field of EA management by offering a systematic and scalable solution to automating the validation of EA principles. By bridging the gap between natural language principles and graphical EA models, the ontology-based valida- tion approach empowers organizations to align their strategic objectives with operational realities, fostering more effective and resilient enterprise systems.