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ABSTRACT A defining feature of 21st century engineering challenges is their inherent complexity, demanding the convergence of knowledge across diverse disciplines. Establishing consistent methodological foundations for engineering systems remains a challenge—one that both systems engineering and network science have sought to address. Model‐based systems engineering (MBSE) has recently emerged as a practical, interdisciplinary approach for developing complex systems from concept through implementation. In contrast, network science focuses on the quantitative analysis of networks present within engineering systems. This article introduces hetero‐functional graph theory (HFGT) as a conceptual bridge between these two fields, serving as an entry point for both communities. For systems engineers, HFGT preserves the heterogeneity of conceptual and ontological constructs in MBSE, including system form, function, and concept. For network scientists, it provides multiple graph‐based data structures enabling matrix‐based quantitative analysis. The modeling process begins with ontological foundations, where an engineering system is defined as an abstraction and represented with a model. Model fidelity is assessed using four linguistic properties: soundness, completeness, lucidity, and laconicity. A meta‐architecture is introduced to manage the convergence challenges between domain‐specific reference architectures and case‐specific instantiations. Unlike other meta‐architectures, HFGT is rooted in linguistic structures, modeling resources as subjects, system processes as predicates, and operands—such as matter, energy, organisms, information, and money—as objects. These elements are integrated within a system meta‐architecture expressed in the Systems Modeling Language (SysML). The article concludes by offering guidance for further reading. Significance and Practitioner PointsThis article introduces hetero‐functional graph theory (HFGT) as a methodological bridge between the graphical modeling of Model‐Based Systems Engineering (MBSE) and mathematical models founded in network science, dynamic systems, and operations research. For researchers, HFGT provides a rigorous methodological foundation that addresses the complex and heterogeneous interdependencies in systems of systems, overcomes the ontological limitations of multilayer networks, and reconciles the methods for structural analysis, dynamic simulation, and optimization. It addresses a critical gap in the systems science literature by enabling the mathematical synthesis of structural and functional viewpoints of complex engineering systems. For practitioners, HFGT offers a scalable and automatable methodology to translate complex architectural diagrams into computable mathematical models. This allows for proactive and self‐consistent design and analysis of the structural and dynamic properties of a system‐of‐systems from the earliest phases of the system life cycle to its final implementation. Ultimately, the paper provides a conceptual introduction to HFGT, demonstrating a foundational language for engineering systems that ensures architectural descriptions are not just visual aids, but mathematically actionable blueprints. 

Evolutionary mechanisms have enabled humans to transform Earth systems. Because the resulting Anthropocene systems are highly interdependent and dynamically evolving, often with accelerating rates of cultural and technological evolution, One Earth and One Health must be framed and addressed in a holistic fashion. An agile, evolutionary, system-of-systems, convergence paradigm, which is based on a partially quantifiable, scientifically falsifiable theoretical framework, can be used to systematically identify, decompose, characterize, and then converge a nested, evolutionary ensemble of geophysical, biophysical, sociocultural, and sociotechnical systems. The paradigm includes individual organisms (spanning plants, fungi, and animals) engaging in niche construction in a global meta-ecosystem that integrates the deep evolutionary history of all Anthropocene systems. To coherently span the vast range of scales, the paradigm is divided into a somatic realm (externally oriented with respect to individual organisms) that can be applied at global, regional, urban, and local scales, as well as a visceral realm (internally oriented with respect to individual organisms) that includes organs, cells, organelles, genes, and molecules. The paradigm requires a causally coherent evolutionary framework, cross-scale, modular, and hierarchical conceptual models (based on a common language and reconciled ontology), with agile, extensible, and scalable computational frameworks, an associated decision-support system, and an educational pedagogy. 

ABSTRACT This study introduces a dual‐layer protocol for diagnosing how formal institutional designs are implemented in practice in complex governance systems. The protocol builds two linked process maps; one for the formal rules and procedures (rules‐in‐form) and one for the routines actors actually follow in practice (rules‐in‐use). We adapt Systems Modeling Language (SysML), a graphical notation from systems engineering for specifying and analyzing complex socio‐technical systems, to represent both formal workflows and observed rules‐in‐use, and then overlay the two maps to identify divergence nodes where practice bypasses, supplements, or otherwise alters formally prescribed processes. Using Chesapeake Bay watershed governance as an illustrative case, the method shows how drift, layering, conversion, and displacement become visible through recurring divergences in data submission, model review, and approval routines, including socio‐technical artifacts such as data schemas, model parameters, and verification procedures. By producing transparent, empirically checkable visualizations linked to qualitative and documentary evidence, the protocol supports comparative institutional diagnostics and more targeted inquiry into where formal–informal gaps emerge and how they operate in collaborative governance. The study contributes to institutional analysis and policy process research by making visible the mechanisms through which gradual institutional change unfolds in collaborative governance and by offering a replicable way to represent implementation architecture and make socio‐technical dependencies more readily inspectable through an open systems‐engineering notation.