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Over the past decades, the definition of system has eluded researchers and practitioners. We reviewed over 100 definitions of system to understand the variations and establish a framework for a widely acceptable system definition or a family of system definitions. There is much common ground in different families of definitions of system, but there are also important and significant ontological differences. Some differences stem from the variety of belief systems and worldviews, while others have risen within particular communities. Both limit the effectiveness of system communities’ efforts to communicate, collaborate, and learn from others’ experience. We consider three ontological elements: (1) a worldview-based framework for typology of different system types and categories, (2) key system concepts that are fundamental to the various system types and categories, and (3) appropriate language for the target audience. In this work, we establish the ontological framework, list key concepts associated with different types of system, and point to a direction for agreeing on an integrated set of system definitions in a neutral language consistent with the framework. The definitions are compatible with both the realist and constructivist worldviews, covering real (physical, concrete) and conceptual (abstract, logical, informatical) systems, which are both human-made (artificial) and naturally occurring, using language acceptable to a wide target stakeholder audience. The contribution of this paper is setting up an ontologically founded framework of system typologies, providing definitions for system, and identifying the issues involved in achieving a widely accepted definition or family of definitions of system.

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... Every process involves an interaction between hard , technical systems (which might be very basic equipment/products to be used or very complex technical systems to be operated) and soft , social systems (the behaviour of people who play various roles in the 2 As Dori and Sillito pointed out [10], the concept system is used in science since the times of Aristotle, who affirmed that the whole is something over and above its parts, and not just the sum of them all. ( [11], quoted in [10], p. 209). ...
... Every process involves an interaction between hard , technical systems (which might be very basic equipment/products to be used or very complex technical systems to be operated) and soft , social systems (the behaviour of people who play various roles in the 2 As Dori and Sillito pointed out [10], the concept system is used in science since the times of Aristotle, who affirmed that the whole is something over and above its parts, and not just the sum of them all. ( [11], quoted in [10], p. 209). Despite this, the definition of system in modern science is still not universally codified. ...
... Despite this, the definition of system in modern science is still not universally codified. [10] Similarly, also modern Systems Engineering doesn't have a universally codified definition. Here Systems Engineering will be defined as . . . ...
Technical Report
Open source information, here defined as “publicly available information that anyone can lawfully obtain by request, purchase, or observation” is playing an increasing role in treaty monitoring, compliance verification and control. The increasing availability of data from a growing number of sources on a vast range of topics has the potential to provide cues about complex programmes subject to international treaties such as the Treaty on the Non- Proliferation of Nuclear Weapons (NPT). This report suggests a system’s thinking view of open source analysis in support to non-proliferation analysis, identifying the possible dimensions (hard/soft/context) involved and discussing different types of scenarios an open source analyst might face. Modelling a nuclear engineering programme by explicitly acknowledging the peculiarities of its hard and soft layers allows the analyst to consider which are the types of insights that each layer can provide and which is the best tool/technique to investigate them. Once a particular analysis is set, the analyst might face different types of analysis scenarios, according to the type of the problem to be tackled and the type of data at his disposal. An open source analyst in support of non-proliferation will also have to handle many different forms of uncertainties, whose proper understanding is critical for the analyst to perform dependable assessments and for the decision maker to take properly informed decisions. A system’s thinking approach to open source analysis has the potential to integrate synergically with the other tools available in the international treaty monitoring toolkit, helping in increasing the international community’s confidence in its ability to detect an undeclared proliferation programme.
... As a result, the same word may mean different things in different contexts, and different words are used in different domains to mean the same thing (Schindel, 1997). Such different interpretations of SE concepts by individuals and communities can lead to the misunderstanding and misinterpretation in the development of systems (Hallberg et al., 2014;Dori and Sillitto, 2017). (4) Inefficient collaborations caused by the misunderstanding and misinterpretation. ...
... These issues are magnified when previously separate communities work together. Miscommunication and lack of mutual understanding of key concepts in SE can potentially lead to dire consequences (Dori and Sillitto, 2017). ...
... The study of what a system means to the SE domain has been continuously debated. Among them, Dori and Sillitto (2017) establish an integrative ontological framework to classify and map over 100 definitions of 'system'. They conclude that one single definition of a system cannot be both precise enough, to be useful, and general enough, to satisfy the widest possible range of systems community. ...
... Having a comprehensive entrepreneurship competence model to understand how knowledge, skills and attitudes are related and developed and how to systematically support their development in educational settings is critical. Relying on systems theory (e.g., Dori and Sillitto 2017;von Bertalanffy 1968;Ackoff 1981), the comprehensive entrepreneurship competence model should describe the sub-competencies that are interrelated with each other and address the need to be successful in entrepreneurial activities of value creation in different contexts. It is, therefore, necessary to consider several important characteristics of competencies when creating such a model. ...
... Relying on previous experience in the formation of holistic competence models (e.g., Le Deist and Winterton 2005;Mulder et al. 2009;Rychen and Salganik 2003;Vaidya 2014), all these sub-competencies in the CECM form the key competence of life-long learning in entrepreneurship, which is essential for all citizens in society (European Commission 2006, 2018. Therefore, the creation of CECM is supported by the systems theory (e.g., Dori and Sillitto 2017;von Bertalanffy 1968;Ackoff 1981) helping to explain that the model describes a purposeful (meant to carry out entrepreneurial activities) structure of sub-competencies that are interrelated with each other and satisfy individuals' need to be successful in the entrepreneurial activities of value creation in different fields and contexts. ...
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The development of entrepreneurship competence considering a broad view of entrepreneurship requires a systematic approach to determine the validated content of learning and methodological basis for supporting learners’ entrepreneurial attitudes and behaviour. There is still relatively little research in this area at all levels of education. Addressing entrepreneurship competence as key competence of lifelong learning allows to broaden the understanding and describe the development of different aspects of entrepreneurship competence through meaningful and supportive interactions in the learning environment. This will allow a better understanding of how to support entrepreneurship competence in various courses and age groups. In this article, a framework of entrepreneurship competence called the Comprehensive Entrepreneurship Competence Model (CECM) is proposed. The development of an entrepreneurship competence model relies on the theory of systems thinking. The CECM model focuses on the developmental perspective (fundamental processes of human development) that is not emphasised in other models. The article also suggests how to support the development of entrepreneurship competence systematically at all levels of education through embedding entrepreneurship competence into the curricula, study programmes of different subjects and overall learning processes.
... Evagorou et al. (2009) described system thinking as "a method of seeing systems from a broad perspective". Dori and Sillitto (2017) stated in their study that "complexity decisionmaking, especially with holistic or system approach. The holistic approach of system thinking is claimed to improve the quality of decision processes". ...
... The study explored the possibility of comparing and merging the tools, the methodologies and framework from system engineering to the human-centered design. The definition of system and system engineering are varied (Dori & Sillitto, 2017). There are many different types of creative processes, tools and theories in the field of human-centered design, design thinking, and system engineering. ...
Conference Paper
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The purpose of the study is to solve the systemic challenge on campus—“How might we create an informative yet delightful campus tour experience for students, visitors and university in the lens of service design?” by applying Object-Process Methodology (OPM) in the field of the system engineering and human-centered design. This study contributes to design research through the seamless combination and comparison of select methodologies from the system engineering and design thinking fields to solving the challenges faced by university campuses. In particular, the study utilized OPM to decompose the whole campus tour system into four main components: object, process, link and status, which helps analyze the system in the lens of insideout perspective. The results showed that using OPM inspired the individuals to revisit and to clarify the internal organization structure and its relationships in the context of the service provider – the university. Within the sub-systems, the study utilized a human-centered design: target group interviews, journey mapping, concept prototyping, scenario experiment and service design refinement to identify the core cause and recommend five key touchpoints and its design suggestions across the campus tour journey. In a way, applying a humancentered design is to view the challenge in the lens of the outside-in perspective, which underlines the user needs in the context of service receiver – visitors, students, and investors. The example not only successfully redesigns and improves the existing campus tour experience from both the service receiver and the service provider, but also perfectly curate OPM with the human-centered design to scale the impact of the project.
... Herein we provide a working definition of system to place our use of the term systems thinking in the context of science, technology, and engineering education: (1) a system is an entity made up of interacting parts; (2) this entity provides a function for a specific intended purpose, or end (in engineering), or outcome (in science); (3) this purpose or outcome is achieved through the interaction of all (or the main) parts of the system; (4) the interaction between the system parts are maintained by cause and effect relationships; (5) systems feature multiple levels of system integration; (6) each level of system integration exhibits whole-system properties not belonging to parts or combination of parts at lower levels of the system; (7) in engineering, systems are artificial, while in science, natural phenomena can be described as systems; and (8) artificial systems include means-ends relationships, while natural phenomena do not (Assaraf & Orion, 2005;Batzri, Assaraf, Cohen, & Orion, 2015;Checkland, 2000;de Vries, 2018b;Dori, & Sillitto, 2017;Svensson, 2018). ...
Systems thinking is an important skill in science and engineering education. Our study objectives were (1) to create the basis for a systems thinking language common to both science education and engineering education, and (2) to apply this language to assess science and engineering teachers’ systems thinking. We administered two assignments to teacher teams: first, modelling the same adapted scientific text, and second, modelling a synthesis of peer-reviewed articles in science and engineering education, with teams selecting a topic from a list and summarising them. We assessed those models using a rubric for systems thinking we had developed based on our literature review of this topic. We found high interrater reliability and validated the rubric’s theoretical construct for the system aspects of function, structure and behaviour. We found differences in scores between the assignments in favour of the second assignment, for two attributes of systems thinking: ‘expected outcome/intended purpose’ and ‘main object and its sub-objects’. We explain the first attribute difference as stemming from the modellers’ domain expertise as science or engineering teachers, rather than as scientists or engineers, and the second attribute difference – from the larger amount of information available for modelling the articles synthesis assignment. The theoretical contribution of this study lies in the definition of the systems thinking construct as a first step in establishing a common language for the science education and engineering education communities. The study's methodological contribution lies in the rubric we developed and validated, which can be used for assessing the systems thinking of teachers and potentially also of undergraduate students.
The success of systems engineering (SE) efforts to solve development issues benefit from the mutually advantageous relationship between academia and practice. This relationship can be threatened by lag in adoption and differences in focus between the two worlds. In an effort to help maintain alignment between SE research and practice, a 2‐day workshop was held at the University of Alabama in Huntsville on research needs in SE. The workshop was attended by individuals from academia, the Department of Defense, NASA, and the aerospace industry. This paper presents summaries of the discussions that took place, as well as possible research questions informed by the results of the workshop. The workshop consisted of an introductory roundtable and three breakouts sessions focusing on requirements, verification, and validation; configuration and data management; and systems acquisition and design. Several topics emerged as important concepts for future research, and research questions were developed relating to model‐based systems engineering (MBSE), requirements, modeling, sociotechnical issues, and education.
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The System Definition Survey issued to INCOSE Fellows in December 2016 revealed at least five radically distinct worldviews on Systems within a relatively small, but moderately representative, part of the INCOSE community. We describe and analyse the survey results, and comment on differences between the responses from the Fellows and the responses to a similar survey issued to the System Science Working Group a month later. Then we discuss how the different worldviews on “system” revealed by the surveys map onto different areas of the set of system definitions described in a previous paper. We conclude that all the worldviews identified offer useful perspectives for systems engineering, and that Systems Engineers need the flexibility to adopt different worldviews for different situations, or at least to act “as if” different worldviews are true in different situations.
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INCOSE's definition of systems engineering was compared to the aspirations set out in the INCOSE Systems Engineering Vision 2025 for systems engineering as it ought to be to address modern challenges. Doing this led us to three fundamental realisations. First, while “20th century systems” were, for the most part, “deterministic” or nearly so, 21st century systems are on the other hand increasingly non‐deterministic, adaptive or “evolutionary.” Second, while “20th Century systems engineering management” was implicitly based on a “command and control” paradigm, 21st Century systems engineering, to be successful, will usually need to use a more collaborative leadership paradigm. And third, that while 20th Century systems were largely “single systems”, designed to “solve” specific problems, 21st Century systems are almost invariably networked, and are parts of complex extended enterprises with multiple, often conflicting, stakeholder objectives, that are intimately related to complex societal challenges. We used elements of soft systems methodology (SSM) to understand the implication and consequences of the paradigm shift implied by these realisations. A revised strawman definition of systems engineering is offered for consideration by INCOSE, showing the changes that would be required to take these and related factors into account.
Systems engineering is evolving from a largely text‐based endeavour towards a more graphical and model‐based approach. While modelling of the structural aspects of a system is well developed, the modelling of requirements is still evolving. This paper proposes a traceable method for transforming textual functional requirements or business activities into required behaviours and proposes a multiscale approach to refining the behavioural descriptions into “atomic” behavioural requirements which can be satisfied either by existing systems or which can form the basis for development of new subsystems.
The concept of Health Systems is ubiquitous in the healthcare literature. However, the question ‘what is a Health System’ is not easy to answer. The emerging field of Health Systems Design is by nature multi-disciplinary, involving several disciplines with different ontological commitments and diverse perspectives and interpretations of health and system. To avoid confusions in communication and facilitate engagement between the design and health communities, it is important to begin an open exploration of the fundamental concepts of Health Systems. This paper is a first step in that endeavour
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Advancing Industry 4.0 concepts by mapping the product of the automotive industry on the spectrum of Cyber Physical Systems, we immediately recognise the convoluted processes involved in the design of new generation vehicles. New technologies developed around the communication core (IoT) enable novel interactions with data. Our framework employs previously untapped data from vehicles in the field for intelligent vehicle health management and knowledge integration into design. Firstly, the concept of an inter-disciplinary artefact is introduced to support the dynamic alignment of disparate functions, so that cyber variables change when physical variables change. Secondly, the axiomatic categorisation (AC) framework simulates functional transformations from artefact to artefact, to monitor and control automotive systems rather than components. Herein, an artefact is defined as a triad of the physical and engineered component, the information processing entity, and communication devices at their interface. Variable changes are modelled using AC, in conjunction with the artefacts, to aggregate functional transformations within the conceptual boundary of a physical system of systems.
We aim to lend insights into “what” constitutes design rationale and “how” to capture these. We restrict the scope of design rationale to the cases of failures observed while testing real engineered systems. We propose a model as an integration of a system hierarchy, a causal chain, and a causality model to cast multiple views of design rationale. The model is structured into databases using a newly introduced version of design structure matrices and supported using a web interface called CRIS4P, which is deployed at a space agency. We report a case example from the spacecraft domain and benchmark the proposed model against IBIS‐FAD model.
The literature shows disparities in how fundamental systems engineering concepts in the area of requirements engineering, such as stakeholder needs, system requirements , requirements elicitation, requirements derivation, and requirements decomposition , are used within the communities-of-practice and in research. Such disparities can lead to conceptual and application inconsistencies, which have been shown to contribute to the formulation of poor requirements. In this paper, such concepts are articulated using systems theory as the underlying theoretical framework. The concepts of problem space, solution space, open system, and closed system are central to this work. It is argued that the proposed articulations facilitate avoiding usage disparity, ultimately resulting in better formulation of requirements. These articulations are supported by in-depth examples that comprehensively cover different types of needs and requirements, and provide step-by-step insights into how elicitation, derivation, and decomposition occur within a problem formulation effort.
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In all areas of scientific study, definitions are used to describe the meaning of terms. Thus, a good set of definitions aids the scientific process by enabling researchers to communicate in a common language. In this regard, the Systems Engineering community has allocated significant effort to understanding the nature and scope of common definitions of a system. However, less attention has been given to formally examining whether these common definitions of a system are adequate. In this paper, we argue that the common definitions of a system are limited in their ability to adequately define a system's boundary. Furthermore, we argue that the common definitions of a system rely on context and prior understanding to communicate the boundary of a system. Finally, by using concepts from philosophy and mathematical logic, we show that the common definitions of a system are nominal in their ability to define a system's boundary.
Research is increasingly under the spotlight to demonstrate impact as well as ‘World Class’ quality. Impact measures were introduced into the United Kingdom’s Research Excellence Framework in 2014, and are being adopted in other countries. However, impact is a concept that is both loosely applied and often contested. It needs unpacking to build understanding about how it can be effectively evaluated. This article uses findings from a subsample of 1309 research-based case studies in leadership, governance and management submitted to the Research Excellence Framework. The mixed-method study used Complex Adaptive Systems as a lens to explore perspectives of impact as a consequence of research, as a process and as an emerging concept. We describe some of the rich patterns of impact practices, mechanisms for exchange, connections with context, and types of measures, used to evidence impact. The article helps to illuminate the complexity of impact and implications for its evaluation.
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What do the Wall Street "Flash Crash", the 2003 invasion of Iraq, and the community on the remote Scottish island of St Kilda, have in common? They're all complex systems that failed in unexpected ways because critical interdependencies weren't understood properly. Why do so many big projects overspend and over-run? They're managed as if they were merely complicated when in fact they are complex. They're planned as if everything was known at the start when in fact they involve high levels of uncertainty and risk. In a rapidly changing world, how do you plan for success and create adaptable, resilient, sustainable systems that will achieve their purpose without adverse unintended consequences? Based on the author's extensive experience as a practical engineer and thought-leader in the systems business, this book provides a highly readable synthesis of the foundations for architecting systems. Starting from a clear set of systems principles and insights into the nature of complexity, the "six step architecting process" will help you to unravel complexity and to architect systems of any type, scale and socio-technical mix. It's illustrated with numerous examples ranging from familiar domestic situations through software-dependent products and services to ultra-large-scale sociotechnical networks spanning the planet. This book is required reading for engineers, managers, clients and leaders of change faced with the challenges of developing systems for the 21st Century. It gives architecting teams and their stakeholders a common understanding of the why, the what, and the how of architecting systems fit for the future.
Model-Based Systems Engineering (MBSE), which tackles architecting and design of complex systems through the use of formal models, is emerging as the most critical component of systems engineering. This textbook specifies the two leading conceptual modeling languages, OPM-the new ISO 19450, composed primarily by the author of this book, and OMG SysML. It provides essential insights into a domain-independent, discipline-crossing methodology of developing or researching complex systems of any conceivable kind and size. Combining theory with a host of industrial, biological, and daily life examples, the book explains principles and provides guidelines for architecting complex, multidisciplinary systems, making it an indispensable resource for systems architects and designers, engineers of any discipline, executives at all levels, project managers, IT professional, systems scientists, and engineering students. © Springer Science+Business Media New York 2016. All rights reserved.
An increasing number of psychiatrists recognize the need of psychiatry for an integrative theory to provide a basis for their diagnostic and therapeutic actions. General living systems theory is a conceptual framework within which the biological and social approaches to the study of living things are logically integrated with the physical sciences. This theoretical integration and the empirical testing of hypotheses which it requires, can provide to psychiatry the theoretical and empirical support that other medical specialties find in cellular biology, physiology, and biochemistry.
Developmental and child psychology remains a vital area in modern psychology. This comprehensive set covers a broad spectrum of developmenal issues, from the psychology of the infant, the family, abilities and disabilities, children's art, imagination, play, speech, mental development, perception, intelligence, mental health and education. In looking at areas which continue to be very important today, these volumes provide a fascinating look at how approaches and attitudes to children have changed over the years. The set includes nine volumes by key development psychologist Jean Piaget, as well as titles by Charlotte Buhler and Susan Isaacs.
Living systems theory identifies basic principles that underlie the structure and processes of living things and relates them to the nonliving physical world, integrating and bringing order to the ever-growing mass of empirical data about them. In addition, living systems models and methodology are useful in empirical research on the great variety of systems of interest to psychology and related fields and in study of individual systems at any of the eight levels of living systems.
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