SEBoK Part 2 is a guide to knowledge associated with systems, particularly knowledge relevant to systems engineering (SE). This knowledge is included in the Guide to the SE Body of Knowledge (SEBoK) to help systems engineers benefit from an understanding of the broader context for their discipline, in terms of theories and practices of systems science and other fields of systems practice. It is also hoped that by including the wider systems science context of SE we will make SE knowledge more accessible to a wider audience outside of its traditional domains.
Knowledge Areas in Part 2
Each part of the SEBoK is divided into knowledge areas (KAs), which are groupings of information with a related theme. Part 2 contains the following KAs:
• Systems Fundamentals
• Systems Science
• Systems Thinking
• Representing Systems with Models
• Systems Approach Applied to Engineered Systems
Most systems engineers are practitioners, applying processes and methods that have been developed and evolved over decades. SE is a pragmatic approach, inherently interdisciplinary, yet specialized.
Systems engineers usually work within a specific domain, using processes and methods that are tailored to their domain’s unique problems, constraints, risks and opportunities. These processes and methods have been found to capture domain experts’ knowledge of the best order to tackle issues as a problem in the particular domain is approached.
Specific domains in which systems approaches are used and adapted include
• Technology products, integrating multiple engineering disciplines
• Information-rich systems, e.g. command & control, air traffic management etc
• Platforms, e.g. aircraft, civil airliners, cars, trains, etc
• Organizational and enterprise systems, which may be focused on delivering service or capability
• Civil engineering/infrastructure systems, e.g. roads networks, bridges, builds, communications networks, etc.
The specific skill-sets for each domain and system scale may be quite different. However there are certain underlying unifying principle based on systems science and systems thinking that will improve the effectiveness of the systems approach in any domain. In particular, shared knowledge of systems principles and terminology will enable communication and improve our ability to integrate complex systems that span traditional domain boundaries (Sillitto 2012). This integrated approach is increasingly needed to solve today’s complex system challenges, but as these different communities come together they can find that assumptions underpinning their world-views are not shared.
To bridge between different domains and communities of practice, we need a well-grounded definition of the “intellectual foundations of systems engineering”, and a common language to describe the relevant concepts and paradigms. We need to look beyond systems engineering to achieve this. An integrated systems approach for solving complex problems needs to combine elements of systems science, systems thinking and systems approaches to practice, ranging from the technical-systems focus that has been dominant in systems engineering to the learning-systems focus of social systems intervention. An integrated systems approach needs to provide a framework and language that allow different communities, with highly divergent world-views and skill sets, to work together for a common purpose.
The Systems Praxis Framework
The term “systems praxis” refers to the entire intellectual and practical endeavor for creating holistic solutions to today’s complex system challenges. Praxis (glossary) is defined as “translating an idea into action” (Wordnet) and the best holistic approach to a given complex challenge may require integrating appropriate theory and appropriate practice from a wide variety of sources. Systems praxis requires many communities to work together. To work together we must first communicate; and to communicate, we must first connect.
A framework for unifying systems praxis was developed by members of International Council on Systems
Engineering (INCOSE) and International Society for the System Sciences (ISSS) (International Federation for Systems Research (IFSR) 2012)) as the first step towards a “common language for systems praxis”.
This Systems Praxis Framework is included here because it represents current thinking on the foundations and common language of systems engineering, making the concepts and principles of systems thinking and practice accessible to anyone applying a systems approach to engineered system problems. This framework and thinking have been used to help organize the guide to systems knowledge in the SEBoK.
In this framework, the following elements are connected:
Systems Thinking is the core integrative element of the framework. It binds the foundations, theories and representations of systems science together with the hard, soft and pragmatic approaches of systems practice. In systems praxis, as in any practical discipline underpinned by science, there is constant interplay between theories and practice, with theory informing practice and outcomes from practice informing theory. Systems thinking is the ongoing activity of assessing and appreciating the system context, and guiding appropriate adaptation, throughout the praxis cycle.
Integrative Systems Science has a very wide scope and is grouped into three broad areas:
• Foundations, which help us to organize knowledge, learning and discovery, and include: meta-theories of methodology; ontology; epistemology; axiology; praxiology (theory of effective action); teleology, semiotics & semiosis; category theory; etc.
• Theories about systems, abstracted from domains and specialisms so as to be universally applicable: general system theory; systems pathology; complexity; anticipatory systems; cybernetics; autopoiesis; living systems; science of generic design; organization theory; etc.
• Representations and corresponding theories we can use to describe, explore, analyze, and make predictions about systems and their wider contexts, whether in terms of models; dynamics; networks; cellular automata; life cycles; queues; graphs; rich pictures; narratives; games and dramas; agent-based simulations; etc.
Systems Approaches to Practice aim to act on the real world to produce desired outcomes without adverse unintended consequences so practice needs to draw on the wide range of knowledge appropriate to the system-of-interest and its wider context. No one branch of systems science or practice provides a satisfactory explanation for all aspects of a typical system “problematique”, a more pragmatic approach is needed.
• Hard approaches suited to solving well-defined problems with reliable data and clear goals, using analytical methods and quantitative techniques. Strongly influenced by “machine” metaphors, they focus on technical systems, objective complexity, and optimization to achieve desired combinations of emergent properties. They are based on “realist” and “functionalist” foundations and worldview.
• Soft approaches suited to structuring problems involving incomplete data, unclear goals, and open inquiries, using a “learning system” metaphor; focus on communication, intersubjective complexity, interpretations and roles; and draw on subjective and “humanist” philosophies with constructivist and interpretivist foundations.
Pragmatic (Pluralist or Critical) approaches judiciously select an appropriate set of tools and patterns that will give sufficient and appropriate insights to manage the issue at hand, applying multiple methodologies drawn from different foundations as appropriate to the situation. Heuristics, boundary critiques, model unfolding, etc, enable understanding of assumptions, contexts, and constraints, including complexity due to different stakeholders’ values and valuations. An appropriate mix of “hard” “soft” and custom methods draws on both systems and domain-specific traditions. Systems may be viewed as networks, societies of agents, organisms, ecosystems, rhizomes, discourses, machines, etc.
The set of “clouds” that collectively represents systems praxis is part of a wider ecosystem of knowledge, learning and action. Successful integration with this wider ecosystem is key to success with real world systems. Systems science is augmented by “hard” scientific disciplines such as physics and neuroscience, and by formal disciplines such as mathematics, logic and computation; it is both enhanced by, and used in, humanistic disciplines such as psychology, culture, and rhetoric, and pragmatic disciplines, such as accounting, design, and law. Systems practice depends on measured data and specified metrics relevant to the problem situation and domain; on solicitation of local values and knowledge; and on pragmatic integration of experience, legacy practices, and discipline knowledge.
Integrative Systems Science allows us to identify, explore and understand patterns of complexity through contributions from the foundations, theories and representations of systems science and other disciplines relevant to the “problematique”.
Systems Approaches to Practice address complex problems and opportunities using methods, tools, frameworks, patterns, etc, drawn from the knowledge of integrative systems science, while observation of the results of systems practice enhances the body of theory.
Systems Thinking binds the two together through appreciative and reflective practice using systems concepts, principles, patterns, etc.