A Metamodel for ilities

Abstract

This paper addresses the transformation of systems architecture from intuition-driven to scientifically grounded practices, highlighting the importance of structured frameworks due to increasing complexity in technology systems. It advocates for a “scientification” of architecture, using quantifiable methods to enhance system ilities. To achieve this, we present a metamodel for use in Model-Based Systems Engineering (MBSE). It serves as a standardized framework to represent architectural elements, support interdisciplinary collaboration, and ensure alignment with stakeholder needs. Principal objectives include enabling rigorous validation, early architectural assessments, and systematic knowledge repositories for predictable design outcomes. The metamodel standardizes architectural concepts and their relationships and promotes a universal understanding and collaborative development of them. It provides a conceptual framework that enables embedding structured scientifically grounded bodies of knowledge and approaches into the systems engineering process, facilitating data-driven decisions, improving transparency, and reducing risks associated with late-stage design decisions. It enables continuous enhancement of bodies of knowledge to support dynamic, scalable, and repeatable engineering processes that keep pace with evolving system demands.