💻IT: Standardization (Definitions)

"The imposition of standards which, in turn, are fixed ways of doing things that are widely recognized." (Roy Rada &  Heather Holden, "Online Education, Standardization, and Roles", 2009)

"Formulation, publication, and implementation of guidelines, rules, methods, procedures and specifications for common and repeated use, aimed at achieving optimum degree of order or uniformity in given context, discipline, or field; standards are most frequently developed on international level; there exist national standardization bodies cooperating with international bodies; standards can be either legally binding or de facto standards followed by informal convention or voluntary standards (recommendations)." (Lenka Lhotska et al,"Interoperability of Medical Devices and Information Systems", 2013)

"A framework of agreements to which all relevant parties in an industry or organization must adhere to ensure that all processes associated with the creation of a good or performance of a service are performed within set guideline." (Victor A Afonso & Maria de Lurdes Calisto, "Innovation in Experiential Services: Trends and Challenges", 2015)

"The development of uniform specifications for materials, products, processes, practices, measurement, or performance, usually via consultation with stakeholders and sanction by a recognized body, providing for improvements in productivity, interoperability, cooperation, and accountability." (Gregory A Smith, "Assessment in Academic Libraries", 2015)

"A process of developing and implementing technical standards based on consensus among various stakeholders in the field. Standardization can greatly assist with compatibility and interoperability of otherwise disparate software components, where consistent solutions enable mutual gains for all stakeholders." (Krzysztof Krawiec et al, "Metaheuristic Design Patterns: New Perspectives for Larger-Scale Search Architectures", 2018)

"The process through which a standard is developed." (Kai Jakobs, "ICT Standardization", 2018)

"Is a framework of agreements to which professionals in an organization must accept to ensure that all processes associated with the creation of a product or service are performed within set guidelines, achieving uniformity to certain practices or operations within the selected environment. It can be seen as a professional strategy to strengthen professional trust and provide a sense of certainty for professionals or it can be interpreted as a way to lose professionalization and as an adjustment to organizational demands." (Joana V Guerra, "Digital Professionalism: Challenges and Opportunities to Healthcare Professions", 2019)

"The process of making things of the same kind, including products and services, have the same basic features and the same requirements." (Julia Krause, "Through Harmonization of National Technical Regulations to More Sustainability in Engineering Business", 2019)

♜Strategic Management: Gap Analysis (Definitions)

"In the managerial planning process, this is the analysis taken following an exercise to determine what improvements in the process are required." (Robert McCrie, "Security Operations Management 2nd Ed.", 2006)

"An assessment of a system in comparison with another system or a set of requirements, listing those items that are not common between them." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A technique to evaluate the current portfolio mix of components and determine changes needed so components may be added, changed, or terminated to rebalance the portfolio." (Project Management Institute, "The Standard for Portfolio Management" 3rd Ed., 2012)

"Describes the difference between current results and consequences and desired results and consequences." (Joan C Dessinger, "Fundamentals of Performance Improvement 3rd Ed", 2012)

"A formal analysis of the differences between what the policy or regulation requires and what’s actually being done in the organization. Used to generate a list of action items required to become compliant with the policy or regulation." (Mark Rhodes-Ousley, "Information Security: The Complete Reference" 2nd Ed., 2013)

"A comparison between the actual outcome and the desired outcome." (Weiss, "Auditing IT Infrastructures for Compliance" 2nd Ed., 2015)

🕸Systems Engineering: Coherence (Just the Quotes)

"Principles taken upon trust, consequences lamely deduced from them, want of coherence in the parts, and of evidence in the whole, these are every where to be met with in the systems of the most eminent philosophers, and seem to have drawn disgrace upon philosophy itself." (David Hume, "A Treatise of Human Nature", 1739-40)

"A system is said to be coherent if every fact in the system is related every other fact in the system by relations that are not merely conjunctive. A deductive system affords a good example of a coherent system." (Lizzie S Stebbing, "A modern introduction to logic", 1930)

"Even these humble objects reveal that our reality is not a mere collocation of elemental facts, but consists of units in which no part exists by itself, where each part points beyond itself and implies a larger whole. Facts and significance cease to be two concepts belonging to different realms, since a fact is always a fact in an intrinsically coherent whole. We could solve no problem of organization by solving it for each point separately, one after the other; the solution had to come for the whole. Thus we see how the problem of significance is closely bound up with the problem of the relation between the whole and its parts. It has been said: The whole is more than the sum of its parts. It is more correct to say that the whole is something else than the sum of its parts, because summing is a meaningless procedure, whereas the whole-part relationship is meaningful." (Kurt Koffka, "Principles of Gestalt Psychology", 1935)

"[…] reality is a system, completely ordered and fully intelligible, with which thought in its advance is more and more identifying itself. We may look at the growth of knowledge […] as an attempt by our mind to return to union with things as they are in their ordered wholeness. […] and if we take this view, our notion of truth is marked out for us. Truth is the approximation of thought to reality […] Its measure is the distance thought has travelled […] toward that intelligible system […] The degree of truth of a particular proposition is to be judged in the first instance by its coherence with experience as a whole, ultimately by its coherence with that further whole, all comprehensive and fully articulated, in which thought can come to rest." (Brand Blanshard, "The Nature of Thought" Vol. II, 1939)

"We cannot define truth in science until we move from fact to law. And within the body of laws in turn, what impresses us as truth is the orderly coherence of the pieces. They fit together like the characters of a great novel, or like the words of a poem. Indeed, we should keep that last analogy by us always, for science is a language, and like a language it defines its parts by the way they make up a meaning. Every word in a sentence has some uncertainty of definition, and yet the sentence defines its own meaning and that of its words conclusively. It is the internal unity and coherence of science which gives it truth, and which makes it a better system of prediction than any less orderly language." (Jacob Bronowski, "The Common Sense of Science", 1953)

"In our definition of system we noted that all systems have interrelationships between objects and between their attributes. If every part of the system is so related to every other part that any change in one aspect results in dynamic changes in all other parts of the total system, the system is said to behave as a whole or coherently. At the other extreme is a set of parts that are completely unrelated: that is, a change in each part depends only on that part alone. The variation in the set is the physical sum of the variations of the parts. Such behavior is called independent or physical summativity." (Arthur D Hall & Robert E Fagen, "Definition of System", General Systems Vol. 1, 1956)

"The essential vision of reality presents us not with fugitive appearances but with felt patterns of order which have coherence and meaning for the eye and for the mind. Symmetry, balance and rhythmic sequences express characteristics of natural phenomena: the connectedness of nature - the order, the logic, the living process. Here art and science meet on common ground." (Gyorgy Kepes, "The New Landscape: In Art and Science", 1956)

"Within the confines of my abstraction, for instance, it is clear that the problem of truth and validity cannot be solved completely, if what we mean by the truth of an image is its correspondence with some reality in the world outside it.  The difficulty with any correspondence theory of truth is that images can only be compared with images.  They can never be compared with any outside reality.  The difficulty with the coherence theory of truth, on the other hand, is that the coherence or consistency of the image is simply not what we mean by its truth." (Kenneth E Boulding, "The Image: Knowledge in life and society", 1956)

"Self-organization can be defined as the spontaneous creation of a globally coherent pattern out of local interactions. Because of its distributed character, this organization tends to be robust, resisting perturbations. The dynamics of a self-organizing system is typically non-linear, because of circular or feedback relations between the components. Positive feedback leads to an explosive growth, which ends when all components have been absorbed into the new configuration, leaving the system in a stable, negative feedback state. Non-linear systems have in general several stable states, and this number tends to increase (bifurcate) as an increasing input of energy pushes the system farther from its thermodynamic equilibrium." (Francis Heylighen, "The Science Of Self-Organization And Adaptivity", 1970)

"To adapt to a changing environment, the system needs a variety of stable states that is large enough to react to all perturbations but not so large as to make its evolution uncontrollably chaotic. The most adequate states are selected according to their fitness, either directly by the environment, or by subsystems that have adapted to the environment at an earlier stage. Formally, the basic mechanism underlying self-organization is the (often noise-driven) variation which explores different regions in the system’s state space until it enters an attractor. This precludes further variation outside the attractor, and thus restricts the freedom of the system’s components to behave independently. This is equivalent to the increase of coherence, or decrease of statistical entropy, that defines self-organization." (Francis Heylighen, "The Science Of Self-Organization And Adaptivity", 1970)

"Early scientific thinking was holistic, but speculative - the modern scientific temper reacted by being empirical, but atomistic. Neither is free from error, the former because it replaces factual inquiry with faith and insight, and the latter because it sacrifices coherence at the altar of facticity. We witness today another shift in ways of thinking: the shift toward rigorous but holistic theories. This means thinking in terms of facts and events in the context of wholes, forming integrated sets with their own properties and relationships."(Ervin László, "Introduction to Systems Philosophy", 1972)

"When loops are present, the network is no longer singly connected and local propagation schemes will invariably run into trouble. [...] If we ignore the existence of loops and permit the nodes to continue communicating with each other as if the network were singly connected, messages may circulate indefinitely around the loops and process may not converges to a stable equilibrium. […] Such oscillations do not normally occur in probabilistic networks […] which tend to bring all messages to some stable equilibrium as time goes on. However, this asymptotic equilibrium is not coherent, in the sense that it does not represent the posterior probabilities of all nodes of the network." (Judea Pearl, "Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference", 1988)

"There are a variety of swarm topologies, but the only organization that holds a genuine plurality of shapes is the grand mesh. In fact, a plurality of truly divergent components can only remain coherent in a network. No other arrangement-chain, pyramid, tree, circle, hub-can contain true diversity working as a whole. This is why the network is nearly synonymous with democracy or the market." (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995)

"Falling between order and chaos, the moment of complexity is the point at which self-organizing systems emerge to create new patterns of coherence and structures of behaviour." (Mark C Taylor, "The Moment of Complexity: Emerging Network Culture", 2001)

"The word 'coherence' literally means holding or sticking together, but it is usually used to refer to a system, an idea, or a worldview whose parts fit together in a consistent and efficient way. Coherent things work well: A coherent worldview can explain almost anything, while an incoherent worldview is hobbled by internal contradictions. [...] Whenever a system can be analyzed at multiple levels, a special kind of coherence occurs when the levels mesh and mutually interlock." (Jonathan Haidt,"The Happiness Hypothesis: Finding Modern Truth in Ancient Wisdom", 2006)

"A system is an interconnected set of elements that is coherently organized in a way that achieves something." (Donella H Meadows, "Thinking in Systems: A Primer", 2008)

"A worldview must be coherent, logical and adequate. Coherence means that the fundamental ideas constituting the worldview must be seen as proceeding from a single, unifying, overarching concept. A logical worldview means simply that the various ideas constituting it should not be contradictory. Adequate means that it is capable of explaining, logically and coherently, every element of contemporary experience." (M G Jackson, "Transformative Learning for a New Worldview: Learning to Think Differently", 2008)

"Each systems archetype embodies a particular theory about dynamic behavior that can serve as a starting point for selecting and formulating raw data into a coherent set of interrelationships. Once those relationships are made explicit and precise, the 'theory' of the archetype can then further guide us in our data-gathering process to test the causal relationships through direct observation, data analysis, or group deliberation." (Daniel H Kim, "Systems Archetypes as Dynamic Theories", The Systems Thinker Vol. 24 (1), 2013)

"Even more important is the way complex systems seem to strike a balance between the need for order and the imperative for change. Complex systems tend to locate themselves at a place we call 'the edge of chaos'. We imagine the edge of chaos as a place where there is enough innovation to keep a living system vibrant, and enough stability to keep it from collapsing into anarchy. It is a zone of conflict and upheaval, where the old and new are constantly at war. Finding the balance point must be a delicate matter - if a living system drifts too close, it risks falling over into incoherence and dissolution; but if the system moves too far away from the edge, it becomes rigid, frozen, totalitarian. Both conditions lead to extinction. […] Only at the edge of chaos can complex systems flourish. This threshold line, that edge between anarchy and frozen rigidity, is not a like a fence line, it is a fractal line; it possesses nonlinearity. (Stephen H Buhner, "Plant Intelligence and the Imaginal Realm: Beyond the Doors of Perception into the Dreaming of Earth", 2014)

"The work around the complex systems map supported a concentration on causal mechanisms. This enabled poor system responses to be diagnosed as the unanticipated effects of previous policies as well as identification of the drivers of the sector. Understanding the feedback mechanisms in play then allowed experimentation with possible future policies and the creation of a coherent and mutually supporting package of recommendations for change."  (David C Lane et al, "Blending systems thinking approaches for organisational analysis: reviewing child protection", 2015)

🕸Systems Engineering: Change (Just the Quotes)

"Every part of the system is so related to every other part that a change in a particular part causes a changes in all other parts and in the total system." (Arthur D Hall, "A methodology for systems engineering", 1962)

"To say a system is 'self-organizing' leaves open two quite different meanings. There is a first meaning that is simple and unobjectionable. This refers to the system that starts with its parts separate (so that the behavior of each is independent of the others' states) and whose parts then act so that they change towards forming connections of some type. Such a system is 'self-organizing' in the sense that it changes from 'parts separated' to 'parts joined'. […] In general such systems can be more simply characterized as 'self-connecting', for the change from independence between the parts to conditionality can always be seen as some form of 'connection', even if it is as purely functional […]" (W Ross Ashby, "Principles of the self-organizing system", 1962)

 "The systems approach to problems focuses on systems taken as a whole, not on their parts taken separately. Such an approach is concerned with total - system performance even when a change in only one or a few of its parts is contemplated because there are some properties of systems that can only be treated adequately from a holistic point of view. These properties derive from the relationship between parts of systems: how the parts interact and fit together." (Russell L Ackoff, "Towards a System of Systems Concepts", 1971)

"Every system of whatever size must maintain its own structure and must deal with a dynamic environment, i.e., the system must strike a proper balance between stability and change. The cybernetic mechanisms for stability (i.e., homeostasis, negative feedback, autopoiesis, equifinality) and change (i.e., positive feedback, algedonodes, self-organization) are found in all viable systems." (Barry Clemson, "Cybernetics: A New Management Tool", 1984)

"Systems thinking is a discipline for seeing the 'structures' that underlie complex situations, and for discerning high from low leverage change. That is, by seeing wholes we learn how to foster health. To do so, systems thinking offers a language that begins by restructuring how we think." (Peter Senge, "The Fifth Discipline", 1990)

"Systems thinking is a discipline for seeing wholes. It is a framework for seeing interrelationships rather than things, for seeing patterns of change rather than static 'snapshots'. It is a set of general principles- distilled over the course of the twentieth century, spanning fields as diverse as the physical and social sciences, engineering, and management. [...] During the last thirty years, these tools have been applied to understand a wide range of corporate, urban, regional, economic, political, ecological, and even psychological systems. And systems thinking is a sensibility for the subtle interconnectedness that gives living systems their unique character." (Peter Senge, "The Fifth Discipline", 1990)

"Even though these complex systems differ in detail, the question of coherence under change is the central enigma for each." (John H Holland," Hidden Order: How Adaptation Builds Complexity", 1995)

"Complex systems operate under conditions far from equilibrium. Complex systems need a constant flow of energy to change, evolve and survive as complex entities. Equilibrium, symmetry and complete stability mean death. Just as the flow, of energy is necessary to fight entropy and maintain the complex structure of the system, society can only survive as a process. It is defined not by its origins or its goals, but by what it is doing." (Paul Cilliers,"Complexity and Postmodernism: Understanding Complex Systems", 1998)

"The concept ‘complexity’ is not univocal either. Firstly, it is useful to distinguish between the notions ‘complex’ and ‘complicated’. If a system- despite the fact that it may consist of a huge number of components - can be given a complete description in terms of its individual constituents, such a system is merely complicated. […] In a complex system, on the other hand, the interaction among constituents of the system, and the interaction between the system and its environment, are of such a nature that the system as a whole cannot be fully understood simply by analysing its components. Moreover, these relationships are not fixed, but shift and change, often as a result of self-organisation. This can result in novel features, usually referred to in terms of emergent properties." (Paul Cilliers, "Complexity and Postmodernism: Understanding Complex Systems" , 1998)

"Systems thinking means the ability to see the synergy of the whole rather than just the separate elements of a system and to learn to reinforce or change whole system patterns. Many people have been trained to solve problems by breaking a complex system, such as an organization, into discrete parts and working to make each part perform as well as possible. However, the success of each piece does not add up to the success of the whole. to the success of the whole. In fact, sometimes changing one part to make it better actually makes the whole system function less effectively." (Richard L Daft, "The Leadership Experience", 2002)

"The butterfly effect demonstrates that complex dynamical systems are highly responsive and interconnected webs of feedback loops. It reminds us that we live in a highly interconnected world. Thus our actions within an organization can lead to a range of unpredicted responses and unexpected outcomes. This seriously calls into doubt the wisdom of believing that a major organizational change intervention will necessarily achieve its pre-planned and highly desired outcomes. Small changes in the social, technological, political, ecological or economic conditions can have major implications over time for organizations, communities, societies and even nations." (Elizabeth McMillan, "Complexity, Management and the Dynamics of Change: Challenges for practice", 2008)

"The other element of systems thinking is learning to influence the system with reinforcing feedback as an engine for growth or decline. [...] Without this kind of understanding, managers will hit blockages in the form of seeming limits to growth and resistance to change because the large complex system will appear impossible to manage. Systems thinking is a significant solution." (Richard L Daft, "The Leadership Experience" 4th Ed., 2008)

"Enterprise engineering is an emerging discipline that studies enterprises from an engineering perspective. The first paradigm of this discipline is that enterprises are purposefully designed and implemented systems. Consequently, they can be re-designed and re-implemented if there is a need for change. The second paradigm of enterprise engineering is that enterprises are social systems. This means that the system elements are social individuals, and that the essence of an enterprise's operation lies in the entering into and complying with commitments between these social individuals." (Erik Proper, "Advances in Enterprise Engineering II", 2009)

"Most systems in nature are inherently nonlinear and can only be described by nonlinear equations, which are difficult to solve in a closed form. Non-linear systems give rise to interesting phenomena such as chaos, complexity, emergence and self-organization. One of the characteristics of non-linear systems is that a small change in the initial conditions can give rise to complex and significant changes throughout the system. This property of a non-linear system such as the weather is known as the butterfly effect where it is purported that a butterfly flapping its wings in Japan can give rise to a tornado in Kansas. This unpredictable behaviour of nonlinear dynamical systems, i.e. its extreme sensitivity to initial conditions, seems to be random and is therefore referred to as chaos. This chaotic and seemingly random behaviour occurs for non-linear deterministic system in which effects can be linked to causes but cannot be predicted ahead of time." (Robert K Logan, "The Poetry of Physics and The Physics of Poetry", 2010)

"The fundamental assumption underlying all software projects is that software is easy to change. If you violate this assumption by creating inflexible structures, then you undercut the economic model that the entire industry is based on." (Robert C Martin, "The Clean Coder: A code of conduct for professional programmers", 2011)

"Without precise predictability, control is impotent and almost meaningless. In other words, the lesser the predictability, the harder the entity or system is to control, and vice versa. If our universe actually operated on linear causality, with no surprises, uncertainty, or abrupt changes, all future events would be absolutely predictable in a sort of waveless orderliness." (Lawrence K Samuels, "Defense of Chaos", 2013)

"One of the remarkable features of these complex systems created by replicator dynamics is that infinitesimal differences in starting positions create vastly different patterns. This sensitive dependence on initial conditions is often called the butterfly-effect aspect of complex systems - small changes in the replicator dynamics or in the starting point can lead to enormous differences in outcome, and they change one’s view of how robust the current reality is. If it is complex, one small change could have led to a reality that is quite different." (David Colander & Roland Kupers, "Complexity and the art of public policy : solving society’s problems from the bottom up", 2014)

"Cybernetics studies the concepts of control and communication in living organisms, machines and organizations including self-organization. It focuses on how a (digital, mechanical or biological) system processes information, responds to it and changes or being changed for better functioning (including control and communication)." (Dmitry A Novikov, "Cybernetics 2.0", 2016)

🕸Systems Engineering: Synergy (Just the Quotes)

"The constructive process inheres in all forms of synergy, and the cooperation of antithetical forces in nature always results in making, that is, in creating something that did not exist before. But in the organic world this character of structure becomes the leading feature, and we have synthetic products consisting of tissues and organs serving definite purposes, which we call functions." (Lester F Ward, "Pure Sociology", 1903)

"[...] there is a universal principle, operating in every department of nature and at every stage of evolution, which is conservative, creative and constructive. [...] I have at last fixed upon the word synergy, as the term best adapted to express its twofold character of ‘energy’ and ‘mutuality’ or the systematic and organic ‘working together’ of the antithetical forces of nature. [...] Synergy is a synthesis of work, or synthetic work, and this is what is everywhere taking place. It may be said to begin with the primary atomic collision in which mass, motion, time, and space are involved, and to find its simplest expression in the formula for force, which implies a plurality of elements, and signifies an interaction of these elements." (Lester F Ward, "Pure Sociology", 1903)

"Social structures are the products of social synergy, i.e., of the interaction of different social forces, all of which, in and of themselves, are destructive, but whose combined effect, mutually checking, constraining, and equilibrating one another, is to produce structures. The entire drift is toward economy, conservatism, and the prevention of waste. Social structures are mechanisms for the production of results, and the results cannot be secured without them. They are reservoirs of power." (James Q Dealey & Lester F Ward, "A Text-book of Sociology", 1905)

"The true nature of the universal principle of synergy pervading all nature and creating all the different kinds of structure that we observe to exist, must now be made clearer. Primarily and essentially it is a process of equilibration, i.e., the several forces are first brought into a state of partial equilibrium. It begins in collision, conflict, antagonism, and opposition, and then we have the milder phases of antithesis, competition, and interaction, passing next into a modus vivendi, or compromise, and ending in collaboration and cooperation. […] The entire drift is toward economy, conservatism, and the prevention of waste." (James Q Dealey & Lester F Ward, "A Text-book of Sociology", 1905)

"Synergy is the only word in our language that means behavior of whole systems unpredicted by the separately observed behaviors of any of the system's separate parts or any subassembly of the system's parts." (R Buckminster Fuller, "Operating Manual for Spaceship Earth", 1963)

"Synergy means behavior of whole systems unpredicted by the behavior of their parts taken separately." (R Buckminster Fuller, "Synergetics: Explorations in the Geometry of Thinking", 1975)

"[...] synergy is the consequence of the energy expended in creating order. It is locked up in the viable system created, be it an organism or a social system. It is at the level of the system. It is not discernible at the level of the system. It is not discernible at the level of the system’s components. Whenever the system is dismembered to examine its components, this binding energy dissipates." (J-C Spender, "Organizational Knowledge, Collective Practice and Penrose Rents", 1999)

"There is a multilayering of global networks in the key strategic activities that structure and destructure the planet. When these multilayered networks overlap in some node, when there is a node that belongs to different networks, two major consequences follow. First, economies of synergy between these different networks take place in that node: between financial markets and media businesses; or between academic research and technology development and innovation; between politics and media." (Manuel Castells, "The Rise of the Network Society", 1996)

"With the growing interest in complex adaptive systems, artificial life, swarms and simulated societies, the concept of 'collective intelligence' is coming more and more to the fore. The basic idea is that a group of individuals (e. g. people, insects, robots, or software agents) can be smart in a way that none of its members is. Complex, apparently intelligent behavior may emerge from the synergy created by simple interactions between individuals that follow simple rules." (Francis Heylighen, "Collective Intelligence and its Implementation on the Web", 1999)

"Systems thinking means the ability to see the synergy of the whole rather than just the separate elements of a system and to learn to reinforce or change whole system patterns. Many people have been trained to solve problems by breaking a complex system, such as an organization, into discrete parts and working to make each part perform as well as possible. However, the success of each piece does not add up to the success of the whole. to the success of the whole. In fact, sometimes changing one part to make it better actually makes the whole system function less effectively." (Richard L Daft, "The Leadership Experience", 2002)

"Self-organization can be seen as a spontaneous coordination of the interactions between the components of the system, so as to maximize their synergy. This requires the propagation and processing of information, as different components perceive different aspects of the situation, while their shared goal requires this information to be integrated. The resulting process is characterized by distributed cognition: different components participate in different ways to the overall gathering and processing of information, thus collectively solving the problems posed by any perceived deviation between the present situation and the desired situation." (Carlos Gershenson & Francis Heylighen, "How can we think the complex?", 2004)

"Synergy happens when people, things, or events combine to produce a larger impact than they would if each acted separately." (Thomas Homer-Dixon, "The Upside of Down: Catastrophe, Creativity, and the Renewal of Civilization", 2006)

[synergy:] "Measure describing how one agent or system increases the satisfaction of other agents or systems." (Carlos Gershenson, "Design and Control of Self-organizing Systems", 2007)

"To develop a Control, the designer should find aspect systems, subsystems, or constraints that will prevent the negative interferences between elements (friction) and promote positive interferences (synergy). In other words, the designer should search for ways of minimizing frictions that will result in maximization of the global satisfaction" (Carlos Gershenson, "Design and Control of Self-organizing Systems", 2007)

"Synergy is the combined action that occurs when people work together to create new alternatives and solutions. In addition, the greatest opportunity for synergy occurs when people have different viewpoints, because the differences present new opportunities. The essence of synergy is to value and respect differences and take advantage of them to build on strengths and compensate for weaknesses." (Richard L Daft, "The Leadership Experience" 4th Ed., 2008)

"Synergy occurs when organizational parts interact to produce a joint effect that is greater than the sum of the parts acting alone. As a result the organization may attain a special advantage with respect to cost, market power, technology, or employee." (Richard L Daft, "The Leadership Experience" 4th Ed., 2008)

"In short, synergy is the consequence of the energy expended in creating order. It is locked up in the viable system created, be it an organism or a social system. It is at the level of the system. It is not discernible at the level of the system. It is not discernible at the level of the system's components. Whenever the system is dismembered to examine its components, this binding energy dissipates." (J-C Spender, "Organizational Knowledge, Collective Practice and Penrose Rents", 2009)

"Synergy is defined as the surplus gained by working together. A task which couldn’t be fulfilled by one individual, can be completed by the work of different individuals together. To maximize synergy, first, the initial task is divided into different sub-tasks. Different agents perform different tasks, which is called division of labor. An end product of one work is used for another work, which is called workflow. Finally, everything needs to be put together. We call this aggregation. This isn’t as linear as it looks. At every step in the process it can happen that a task is divided into sub tasks or aggregated with other tasks." (Evo Busseniers, "Self-organization versus hierarchical organization", [thesis] 2018)

🕸Systems Engineering: Networks (Just the Quotes)

"Any pattern of activity in a network, regarded as consistent by some observer, is a system." (Gordon Pask, "The Natural History of Networks", 1960)

"I am using the term 'network' in a general sense, to imply any set of interconnected and measurably active physical entities. Naturally occurring networks, of interest because they have a, self-organizing character, are, for example, a marsh, a colony of microorganisms, a research team, and a man." (Gordon Pask, "The Natural History of Networks", 1960)

"A NETWORK is a collection of connected lines, each of which indicates the movement of some quantity between two locations. Generally, entrance to a network is via a source (the starting point) and exit from a network is via a sink (the finishing point); the lines which form the network are called links (or arcs), and the points at which two or more links meet are called nodes." (Cecil W Lowe, "Critical Path Analysis by Bar Chart", 1966)

"An autopoietic system is organized (defined as a unity) as a network of processes of production (transformation and destruction) of components that produces the components that: (a) through their interactions and transformations continuously regenerate and realize the network of processes (relations) that produce them and, (b) constitute it (the machine) as a concrete unity in the space in which they exist by specifying the topological domain of its realization as such a network." (Francisco Varela, "Principles of Biological Autonomy", 1979)

"Information is recorded in vast interconnecting networks. Each idea or image has hundreds, perhaps thousands, of associations and is connected to numerous other points in the mental network." (Peter Russell, "The Brain Book: Know Your Own Mind and How to Use it", 1979)

"When loops are present, the network is no longer singly connected and local propagation schemes will invariably run into trouble. [...] If we ignore the existence of loops and permit the nodes to continue communicating with each other as if the network were singly connected, messages may circulate indefinitely around the loops and process may not converges to a stable equilibrium. […] Such oscillations do not normally occur in probabilistic networks […] which tend to bring all messages to some stable equilibrium as time goes on. However, this asymptotic equilibrium is not coherent, in the sense that it does not represent the posterior probabilities of all nodes of the network." (Judea Pearl, "Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference", 1988)

"What is a system? A system is a network of interdependent components that work together to try to accomplish the aim of the system. A system must have an aim. Without an aim, there is no system. The aim of the system must be clear to everyone in the system. The aim must include plans for the future. The aim is a value judgment." (William E Deming, "The New Economics for Industry, Government, Education”, 1993)

"Mathematics says the sum value of a network increases as the square of the number of members. In other words, as the number of nodes in a network increases arithmetically, the value of the network increases exponentially. Adding a few more members can dramatically increase the value of the network." (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995)

"The basic principle of an autocatalytic network is that even though nothing can make itself, everything in the pot has at least one reaction that makes it, involving only other things in the pot. It's a symbiotic system in which everything cooperates to make the metabolism work - the whole is greater than the sum of the parts." (J Doyne Farmer, "The Second Law of Organization" [in The Third Culture: Beyond the Scientific Revolution], 1995)

"The only organization capable of unprejudiced growth, or unguided learning, is a network. All other topologies limit what can happen." (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995)

"The multiplier effect is a major feature of networks and flows. It arises regardless of the particular nature of the resource, be it goods, money, or messages." (John H Holland, "Hidden Order - How Adaptation Builds Complexity", 1995)

"The more complex the network is, the more complex its pattern of interconnections, the more resilient it will be." (Fritjof Capra, "The Web of Life: A New Scientific Understanding of Living Systems", 1996)

"The notion of system we are interested in may be described generally as a complex of elements or components directly or indirectly related in a network of interrelationships of various kinds, such that it constitutes a dynamic whole with emergent properties." (Walter F. Buckley, "Society: A Complex Adaptive System - Essays in Social Theory", 1998)

"Remember a networked learning machine’s most basic rule: strengthen the connections to those who succeed, weaken them to those who fail." (Howard Bloom, "Global Brain: The Evolution of Mass Mind from the Big Bang to the 21st Century", 2000)

"[…] most earlier attempts to construct a theory of complexity have overlooked the deep link between it and networks. In most systems, complexity starts where networks turn nontrivial." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)

"[…] networks are the prerequisite for describing any complex system, indicating that complexity theory must inevitably stand on the shoulders of network theory. It is tempting to step in the footsteps of some of my predecessors and predict whether and when we will tame complexity. If nothing else, such a prediction could serve as a benchmark to be disproven. Looking back at the speed with which we disentangled the networks around us after the discovery of scale-free networks, one thing is sure: Once we stumble across the right vision of complexity, it will take little to bring it to fruition. When that will happen is one of the mysteries that keeps many of us going." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)

"One of the key insights of the systems approach has been the realization that the network is a pattern that is common to all life. Wherever we see life, we see networks." (Fritjof Capra, "The Hidden Connections: A Science for Sustainable Living", 2002)

"The networked world continuously refines, reinvents, and reinterprets knowledge, often in an autonomic manner." (Donald M Morris et al, "A revolution in knowledge sharing", 2003)

"Hierarchy adapts knowledge to the organization; a network adapts the organization to the knowledge." (George Siemens, "Knowing Knowledge", 2006)

"Nodes and connectors comprise the structure of a network. In contrast, an ecology is a living organism. It influences the formation of the network itself." (George Siemens, "Knowing Knowledge", 2006)

"If a network is solely composed of neighborhood connections, information must traverse a large number of connections to get from place to place. In a small-world network, however, information can be transmitted between any two nodes using, typically, only a small number of connections. In fact, just a small percentage of random, long-distance connections is required to induce such connectivity. This type of network behavior allows the generation of 'six degrees of separation' type results, whereby any agent can connect to any other agent in the system via a path consisting of only a few intermediate nodes." (John H Miller & Scott E Page, "Complex Adaptive Systems", 2007)

"Networks may also be important in terms of view. Many models assume that agents are bunched together on the head of a pin, whereas the reality is that most agents exist within a topology of connections to other agents, and such connections may have an important influence on behavior. […] Models that ignore networks, that is, that assume all activity takes place on the head of a pin, can easily suppress some of the most interesting aspects of the world around us. In a pinhead world, there is no segregation, and majority rule leads to complete conformity - outcomes that, while easy to derive, are of little use." (John H Miller & Scott E Page, "Complex Adaptive Systems", 2007)

"We are beginning to see the entire universe as a holographically interlinked network of energy and information, organically whole and self-referential at all scales of its existence. We, and all things in the universe, are non-locally connected with each other and with all other things in ways that are unfettered by the hitherto known limitations of space and time." (Ervin László, "Cosmos: A Co-creator's Guide to the Whole-World", 2010)

"The people we get along with, trust, feel simpatico with, are the strongest links in our networks." (Daniel Goleman, "Working With Emotional Intelligence", 2011) 

"Cybernetics is the study of systems which can be mapped using loops (or more complicated looping structures) in the network defining the flow of information. Systems of automatic control will of necessity use at least one loop of information flow providing feedback." (Alan Scrivener, "A Curriculum for Cybernetics and Systems Theory", 2012)

"If we create networks with the sole intention of getting something, we won't succeed. We can't pursue the benefits of networks; the benefits ensue from investments in meaningful activities and relationships." (Adam Grant, "Give and Take: A Revolutionary Approach to Success", 2013) 

"Information is recorded in vast interconnecting networks. Each idea or image has hundreds, perhaps thousands, of associations and is connected to numerous other points in the mental network." (Peter Russell, "The Brain Book: Know Your Own Mind and How to Use it", 2013) 

"All living systems are networks of smaller components, and the web of life as a whole is a multilayered structure of living systems nesting within other living systems - networks within networks." (Fritjof Capra, "The Systems View of Life: A Unifying Vision", 2014)

"Although cascading failures may appear random and unpredictable, they follow reproducible laws that can be quantified and even predicted using the tools of network science. First, to avoid damaging cascades, we must understand the structure of the network on which the cascade propagates. Second, we must be able to model the dynamical processes taking place on these networks, like the flow of electricity. Finally, we need to uncover how the interplay between the network structure and dynamics affects the robustness of the whole system." (Albert-László Barabási, "Network Science", 2016)

"The exploding interest in network science during the first decade of the 21st century is rooted in the discovery that despite the obvious diversity of complex systems, the structure and the evolution of the networks behind each system is driven by a common set of fundamental laws and principles. Therefore, notwithstanding the amazing differences in form, size, nature, age, and scope of real networks, most networks are driven by common organizing principles. Once we disregard the nature of the components and the precise nature of the interactions between them, the obtained networks are more similar than different from each other." (Albert-László Barabási, "Network Science", 2016)

More quotes on "Networks" at the-web-of-knowledge.blogspot.com.

🕸Systems Engineering: Environment (Just the Quotes)

"The change from one stable equilibrium to the other may take place as the result of the isolation of a small unrepresentative group of the population, a temporary change in the environment which alters the relative viability of different types, or in several other ways." (John B S Haldane, "The Causes of Evolution", 1932)

"An isolated system or a system in a uniform environment (which for the present consideration we do best to include as a part of the system we contemplate) increases its entropy and more or less rapidly approaches the inert state of maximum entropy. We now recognize this fundamental law of physics to be just the natural tendency of things to approach the chaotic state (the same tendency that the books of a library or the piles of papers and manuscripts on a writing desk display) unless we obviate it. (The analogue of irregular heat motion, in this case, is our handling those objects now and again without troubling to put them back in their proper places.) (Erwin Schrödinger, "What is Life?", 1944)

"Clearly, if the state of the system is coupled to parameters of an environment and the state of the environment is made to modify parameters of the system, a learning process will occur. Such an arrangement will be called a Finite Learning Machine, since it has a definite capacity. It is, of course, an active learning mechanism which trades with its surroundings. Indeed it is the limit case of a self-organizing system which will appear in the network if the currency supply is generalized." (Gordon Pask, "The Natural History of Networks", 1960)

"Every isolated determinate dynamic system, obeying unchanging laws, will ultimately develop some sort of organisms that are adapted to their environments." (W Ross Ashby, "Principles of the self-organizing system", 1962)

"[...] in a state of dynamic equilibrium with their environments. If they do not maintain this equilibrium they die; if they do maintain it they show a degree of spontaneity, variability, and purposiveness of response unknown in the non-living world. This is what is meant by ‘adaptation to environment’ […] [Its] essential feature […] is stability - that is, the ability to withstand disturbances." (Kenneth Craik, 'Living organisms', "The Nature of Psychology", 1966)

"System theory is basically concerned with problems of relationships, of structure, and of interdependence rather than with the constant attributes of objects. In general approach it resembles field theory except that its dynamics deal with temporal as well as spatial patterns. Older formulations of system constructs dealt with the closed systems of the physical sciences, in which relatively self-contained structures could be treated successfully as if they were independent of external forces. But living systems, whether biological organisms or social organizations, are acutely dependent on their external environment and so must be conceived of as open systems." (Daniel Katz, "The Social Psychology of Organizations", 1966)

"Conventional physics deals only with closed systems, i.e. systems which are considered to be isolated from their environment. [...] However, we find systems which by their very nature and definition are not closed systems. Every living organism is essentially an open system. It maintains itself in a continuous inflow and outflow, a building up and breaking down of components, never being, so long as it is alive, in a state of chemical and thermodynamic equilibrium but maintained in a so-called steady state which is distinct from the latter." (Ludwig von Bertalanffy, "General System Theory", 1968)

"System' is the concept that refers both to a complex of interdependencies between parts, components, and processes, that involves discernible regularities of relationships, and to a similar type of interdependency between such a complex and its surrounding environment." (Talcott Parsons, "Systems Analysis: Social Systems", 1968)

"To adapt to a changing environment, the system needs a variety of stable states that is large enough to react to all perturbations but not so large as to make its evolution uncontrollably chaotic. The most adequate states are selected according to their fitness, either directly by the environment, or by subsystems that have adapted to the environment at an earlier stage. Formally, the basic mechanism underlying self-organization is the (often noise-driven) variation which explores different regions in the system’s state space until it enters an attractor. This precludes further variation outside the attractor, and thus restricts the freedom of the system’s components to behave independently. This is equivalent to the increase of coherence, or decrease of statistical entropy, that defines self-organization." (Francis Heylighen, "The Science Of Self-Organization And Adaptivity", 1970)

"The main object of cybernetics is to supply adaptive, hierarchical models, involving feedback and the like, to all aspects of our environment. Often such modelling implies simulation of a system where the simulation should achieve the object of copying both the method of achievement and the end result. Synthesis, as opposed to simulation, is concerned with achieving only the end result and is less concerned (or completely unconcerned) with the method by which the end result is achieved. In the case of behaviour, psychology is concerned with simulation, while cybernetics, although also interested in simulation, is primarily concerned with synthesis." (Frank H George, "Soviet Cybernetics, the militairy and Professor Lerner", New Scientist, 1973)

"For any system the environment is always more complex than the system itself. No system can maintain itself by means of a point-for-point correlation with its environment, i.e., can summon enough 'requisite variety' to match its environment. So each one has to reduce environmental complexity - primarily by restricting the environment itself and perceiving it in a categorically preformed way. On the other hand, the difference of system and environment is a prerequisite for the reduction of complexity because reduction can be performed only within the system, both for the system itself and its environment." (Thomas Luckmann & Niklas Luhmann, "The Differentiation of Society", 1977)

"General systems theory and cybernetics supplanted the classical conceptual model of a whole made out of parts and relations between parts with a model emphasizing the difference between systems and environments. This new paradigm made it possible to relate both the structures (including forms of differentiation) and processes of systems to the environment." (Thomas Luckmann & Niklas Luhmann, "The Differentiation of Society", 1977)

"There is a strong current in contemporary culture advocating ‘holistic’ views as some sort of cure-all […] Reductionism implies attention to a lower level while holistic implies attention to higher level. These are intertwined in any satisfactory description: and each entails some loss relative to our cognitive preferences, as well as some gain [...] there is no whole system without an interconnection of its parts and there is no whole system without an environment." (Francisco Varela, "On being autonomous: The lessons of natural history for systems theory", 1977)

"Every system of whatever size must maintain its own structure and must deal with a dynamic environment, i.e., the system must strike a proper balance between stability and change. The cybernetic mechanisms for stability (i.e., homeostasis, negative feedback, autopoiesis, equifinality) and change (i.e., positive feedback, algedonodes, self-organization) are found in all viable systems." (Barry Clemson, "Cybernetics: A New Management Tool", 1984)

"Any system that insulates itself from diversity in the environment tends to atrophy and lose its complexity and distinctive nature." (Gareth Morgan, "Images of Organization", 1986)

"All systems evolve, although the rates of evolution may vary over time both between and within systems. The rate of evolution is a function of both the inherent stability of the system and changing environmental circumstances. But no system can be stabilized forever. For the universe as a whole, an isolated system, time’s arrow points toward greater and greater breakdown, leading to complete molecular chaos, maximum entropy, and heat death. For open systems, including the living systems that are of major interest to us and that interchange matter and energy with their external environments, time’s arrow points to evolution toward greater and greater complexity. Thus, the universe consists of islands of increasing order in a sea of decreasing order. Open systems evolve and maintain structure by exporting entropy to their external environments." (L Douglas Kiel, "Chaos Theory in the Social Sciences: Foundations and Applications", 1996)

"In a closed system, the change in entropy must always be 'positive', meaning toward death. However, in open biological or social systems, entropy can be arrested and may even be transformed into negative entropy - a process of more complete organization and enhanced ability to transform resources. Why? Because the system imports energy and resources from its environment, leading to renewal. This is why education and learning are so important, as they provide new and stimulating input (termed neg-entropy) that can transform each of us." (Stephen G Haines, "The Managers Pocket Guide to Systems Thinking & Learning", 1998)

"Neural networks conserve the complexity of the systems they model because they have complex structures themselves. Neural networks encode information about their environment in a distributed form. […] Neural networks have the capacity to self-organise their internal structure." (Paul Cilliers, "Complexity and Postmodernism: Understanding Complex Systems", 1998)

"All systems have a tendency toward maximum entropy, disorder, and death. Importing resources from the environment is key to long-term viability; closed systems move toward this disorganization faster than open systems." (Stephen G Haines, "The Systems Thinking Approach to Strategic Planning and Management", 2000)

"Systems thinking practices the exact opposite of this analytic approach. Systems thinking studies the organization as a whole in its interaction with its environment. Then, it works backwards to understand how each part of that whole works in relation to, and support of, the entire system’s objectives. Only then can the core strategies be formulated." (Stephen G Haines, "The Systems Thinking Approach to Strategic Planning and Management", 2000)

"Systems, and organizations as systems, can only be understood holistically. Try to understand the system and its environment first. Organizations are open systems and, as such, are viable only in interaction with and adaptation to the changing environment." (Stephen G Haines, "The Systems Thinking Approach to Strategic Planning and Management", 2000)

"Entropy [...] is the amount of disorder or randomness present in any system. All non-living systems tend toward disorder; left alone they will eventually lose all motion and degenerate into an inert mass. When this permanent stage is reached and no events occur, maximum entropy is attained. A living system can, for a finite time, avert this unalterable process by importing energy from its environment. It is then said to create negentropy, something which is characteristic of all kinds of life." (Lars Skyttner, "General Systems Theory: Ideas and Applications", 2001)

"The phenomenon of emergence takes place at critical points of instability that arise from fluctuations in the environment, amplified by feedback loops." (Fritjof Capra, "The Hidden Connections: A Science for Sustainable Living", 2002)

"Feedback and its big brother, control theory, are such important concepts that it is odd that they usually find no formal place in the education of physicists. On the practical side, experimentalists often need to use feedback. Almost any experiment is subject to the vagaries of environmental perturbations. Usually, one wants to vary a parameter of interest while holding all others constant. How to do this properly is the subject of control theory. More fundamentally, feedback is one of the great ideas developed (mostly) in the last century, with particularly deep consequences for biological systems, and all physicists should have some understanding of such a basic concept." (John Bechhoefer, "Feedback for physicists: A tutorial essay on control", Reviews of Modern Physics Vol. 77, 2005)

"The single most important property of a cybernetic system is that it is controlled by the relationship between endogenous goals and the external environment. [...] In a complex system, overarching goals may be maintained (or attained) by means of an array of hierarchically organized subgoals that may be pursued contemporaneously, cyclically, or seriatim." (Peter Corning, "Synergy, Cybernetics, and the Evolution of Politics", 2005)

"When defining living systems, the term dynamic equilibrium is essential. It does not imply something which is steady or stable. On the contrary, it is a floating state characterized by invisible movements and preparedness for change. To be in dynamic equilibrium is adapting adjustment to balance. Homeostasis stands for the sum of all control functions creating the state of dynamic equilibrium in a healthy organism. It is the ability of the body to maintain a narrow range of internal conditions in spite of environmental changes." (Lars Skyttner, "General Systems Theory: Problems, Perspective, Practice", 2005)

"Systematic usage of the methods of modern control theory to study physical systems is a key feature of a new research area in physics that may be called cybernetical physics. The subject of cybernetical physics is focused on studying physical systems by means of feedback interactions with the environment. Its methodology heavily relies on the design methods developed in cybernetics. However, the approach of cybernetical physics differs from the conventional use of feedback in control applications (e.g., robotics, mechatronics) aimed mainly at driving a system to a prespecified position or a given trajectory." (Alexander L Fradkov, "Cybernetical Physics: From Control of Chaos to Quantum Control", 2007)

"In physical, exponentially growing systems, there must be at least one reinforcing loop driving growth and at least one balancing feedback loop constraining growth, because no system can grow forever in a finite environment." (Donella H Meadows, "Thinking in Systems: A Primer", 2008)

"In that sense, a self-organizing system is intrinsically adaptive: it maintains its basic organization in spite of continuing changes in its environment. As noted, perturbations may even make the system more robust, by helping it to discover a more stable organization." (Francis Heylighen, "Complexity and Self-Organization", 2008)

"If universality is one of the observed characteristics of complex dynamical systems in many fields of study, a second characteristic that flows from the study of these systems is that of emergence. As self-organizing systems go about their daily business, they are constantly exchanging matter and energy with their environment, and this allows them to remain in a state that is far from equilibrium. That allows spontaneous behavior to give rise to new patterns." (Terry Cooke-Davies et al, "Exploring the Complexity of Projects", 2009)

"To remedy chaotic situations requires a chaotic approach, one that is non-linear, constantly morphing, and continually sharpening its competitive edge with recurring feedback loops that build upon past experiences and lessons learned. Improvement cannot be sustained without reflection. Chaos arises from myriad sources that stem from two origins: internal chaos rising within you, and external chaos being imposed upon you by the environment. The result of this push/pull effect is the disequilibrium [...]." (Jeff Boss, "Navigating Chaos: How to Find Certainty in Uncertain Situations", 2015)

More quotes on "Environment" at the-web-of-knowledge.blogspot.com.

🕸Systems Engineering: Cellular Automata (Definitions)

"Cellular automata are mathematical models for complex natural systems containing large numbers of simple identical components with local interactions. They consist of a lattice of sites, each with a finite set of possible values. The value of the sites evolve synchronously in discrete time steps according to identical rules. The value of a particular site is determined by the previous values of a neighbourhood of sites around it." (Stephen Wolfram, "Nonlinear Phenomena, Universality and complexity in cellular automata", Physica 10D, 1984)

"A mathematical construct and technique that models a system in discrete time and discrete space in which the state of a cell depends on transition rules and the states of neighboring cells." (Charles M Macal, "Agent Based Modeling and Artificial Life", 2009) 

[Cellular automaton:] A spatially-extended dynamical system in which spatially-discrete cells take on discrete values, and evolve according to a spatially-localized discrete-time update rule." (James E Hanson, "Emergent Phenomena in Cellular Automata", 2009)

"A spatiotemporal modeling technique in which a set of rules is applied to determine the state transitions of individual cells based on each cell’s current state and the states of its neighbors." (May Yuan, "Challenges and Critical Issues for Temporal GIS Research and Technologies", 2009) 

"Cellular Automata (CA) are discrete, spatially explicit extended dynamic systems composed of adjacent cells characterized by an internal state whose value belongs to a finite set. The updating of these states is made simultaneously according to a common local transition rule involving only a neighborhood of each cell." (Ramon Alonso-Sanz, "Cellular Automata with Memory", 2009) 

"Cellular automata are dynamical systems that are discrete in space, time, and value. A state of a cellular automaton is a spatial array of discrete cells, each containing a value chosen from a finite alphabet. The state space for a cellular automaton is the set of all such configurations." (Burton Voorhees, "Additive Cellular Automata", 2009) 

"They are dynamical systems that are continuous, local, parallel, synchronous and space and time uniform. Cellular automata are used to model phenomena where the space can be regularly partitioned and where the same rules are used everywhere [...]" (Jerome Durand-Lose, "Universality of Cellular Automata", 2009)

"A discrete model consisting of a grip of cells each of which have a finite number of defined states where the state of a cells is a function of the states of neighboring cells and the transition among states is according to some predefined updating rule. (Brian L Heath & Raymond R Hill, "Agent-Based Modeling: A Historical Perspective and a Review of Validation and Verification Efforts, 2010)

"A cellular automaton is composed of a set of discrete elements - the cells - connected with other cells of the automaton, and in each time unit each cell receives information about the current state of the cells to which it is connected. The cellular automaton evolve according a transition rule that specifies the current possible states of each cell as a function of the preceding state of the cell and the states of the connected cells." (Francesc S Beltran et al, "A Language Shift Simulation Based on Cellular Automata", 2011)

"Cellular automata (CA) are idealizations of physical systems in which both space and time are assumed to be discrete and each of the interacting units can have only a finite number of discrete states." (Andreas Schadschneider et al, "Vehicular Traffic II: The Nagel–Schreckenberg Model" , 2011)

"Cellular automata (henceforth: CA) are discrete, abstract computational systems that have proved useful both as general models of complexity and as more specific representations of non-linear dynamics in a variety of scientific fields." (Francesco Berto & Jacopo Tagliabue, "Cellular Automata", Stanford Encyclopedia of Philosophy, 2012) 

🕸Systems Engineering: Complex Systems (Definitions)

"Roughly, by a complex system I mean one made up of a large number of parts that interact in a nonsimple way." (Herbert Simon, "The Architecture of Complexity", Proceedings of the American Philosophical Society Vol. 106 (6), 1962)

"A complex system is one which possesses mathematical images which are not dynamical systems." (Robert Rosen, On complex systems, European Journal of Operational Research Vol. 30 (2), 1987)

"A complex system is a system formed out of many components whose behavior is emergent, that is, the behavior of the system cannot be simply inferred from the behavior of its components." (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques can not easily handle the problem." (M Jamshidi, Autonomous Control on Complex Systems: Robotic Applications, Current Advances in Mechanical Design and Production VII, 2000)

"A highly coupled system where the outcomes of the system are the result of the interactions that occur between its different components." (David Lyell et al, "Health Systems Simulation", Encyclopedia of Healthcare Information Systems, 2008)

"Network-based systems characterized by feedback-driven flow of information, openness, self-organization, and emergence. (Ani Calinescu & Janet Efstathiou, "Measures of Network Structure", Encyclopedia of Networked and Virtual Organizations, 2008) 

"[a complex system is] a system in which large networks of components with no central control and simple rules of operation give rise to complex collective behavior, sophisticated information processing, and adaptation via learning or evolution." (Melanie Mitchell, "Complexity: A Guided Tour", 2009)

"Systems made of several interconnected simple parts which altogether exhibit a high degree of complexity from each emerges a higher order behaviour." (Radu Mutihac, "Mathematical Modeling of Artificial Neural Networks", Encyclopedia of Artificial Intelligence, 2009)

"CS [complex system] is a system composed of many heterogeneous agents, which are nonlinearly interconnected, while the final emergence of the system is completely different than the individual element`s performance." (Shahrooz V Manesha & Massimo Tadi, "Sustainable urban morphology emergence via complex adaptive system analysis: sustainable design in existing contex", Procedia Engineering 21, 2011)

"A system that exhibits a mutual interdependency of components and for which a change in the input parameter(s) can result in a non-proportional large or small change of the system output." (Alexander Kolker, Management Science for Healthcare Applications, Encyclopedia of Business Analytics and Optimization, 2014) 

"A system whose intricacy impedes the forecasting of its behaviour." (Valentina M Ghinea, "Modelling and Simulation of the Need for Harmonizing the European Higher Education Systems", Handbook of Research on Trends in European Higher Education Convergence, 2014)

"A system which is usually composed of large number of possibly heterogeneous interacting agents, which are seen to exhibit emergent behavior." (Stephen E Glavin & Abhijit Sengupta, "Modelling of Consumer Goods Markets: An Agent-Based Computational Approach", Handbook of Research on Managing and Influencing Consumer Behavior, 2015)

"Complex systems are networks made of a number of components that interact with each other, typically in a nonlinear fashion. Complex systems may arise and evolve through self-organization, such that they are neither completely regular nor completely random, permitting the development of emergent behavior at macroscopic scales." (Hiroki Sayama, "Introduction to the Modeling and Analysis of Complex Systems", 2015)

"The occurrence of new phenomena generated unpredictably by the interaction of simple rules and individual mechanisms that are in constant flux and interaction. Emergence suggests something novel is perpetually emerging at a systems/global level as the world and environment constantly shifts and changes at a mechanistic/local level." (Kathy Sanford & Tim Hopper, "Digital Media in the Classroom: Emergent Perspectives for 21st Century Learners", Handbook of Research on Digital Media and Creative Technologies, 2015)

"A system characterized by the number of the elements that constitute it, and by the nature of the interactions between these elements." (Manuela Piscitelli, "Application of Complexity Theory in Representation of the City", Handbook of Research on Chaos and Complexity Theory in the Social Sciences, 2016)

"A complex system means a system whose perceived complicated behaviors can be attributed to one or more of the following characteristics: large number of element, large number of relationships among elements, non-linear and discontinuous relationship, and uncertain characteristics of elements." (Chunfang Zhou, "Fostering Creative Problem Solvers in Higher Education: A Response to Complexity of Societies", Handbook of Research on Creative Problem-Solving Skill Development in Higher Education, 2017)

"System made up of many interconnected elements on various levels; interactions on lower levels give rise to events on higher levels." (Naomi Thompson & Joshua Danish, "Designing BioSim: Playfully Encouraging Systems Thinking in Young Children", Handbook of Research on Serious Games for Educational Applications, 2017)

🕸Systems Engineering: System (Definitions)

"A system is an imaginary machine invented to connect together in the fancy those different movements and effects which are already in reality performed." (Adam Smith, "The Wealth of Nations", 1776)

"A system is a methodical arrangement of propositions and proofs; and without such arrangement, no distinct and certain knowlege of any subject can be obtained." (Johann G Burckhardt, 1797) 

"A system is a set of objects compromising all that stands to one another in a group of connected relations." (Charles S Peirce, "Cambridge Lectures on Reasoning and the Logic of Things: Detached Ideas on Vitally Important Topics", 1898)

"A system is a whole which is composed of various parts. But it is not the same thing as an aggregate or heap. In an aggregate or heap, no essential relation exists between the units of which it is composed. In a heap of grain, or pile of stones, one may take away part without the other part being at all affected thereby. But in a system, each part has a fixed and necessary relation to the whole and to all the other parts." (James E Creighton, "An Introductory Logic"‎, 1909)

"A system is any portion of the universe set aside for certain specified purposes. For our concern, a system is set aside from the universe in a manner that will enable this system to be built without having to consider the total universe. Therefore, the system is set aside from the universe by its inputs and outputs - its boundaries." (Kay Inaba et al, "A rational method for applying behavioral technology to man-machine system design", 1956)

"A System is a set of elements in interaction." (Ludwig von Bertalanffy, "General System Theory", 1968)

"A system is a set of two or more elements that satisfies the following three conditions. (1) The behavior of each element has an effect on the behavior of the whole. (2) The behavior of the elements and their effects on the whole are interdependent. the way each element behaves and the way it affects the whole depends on how at least one other element behaves. (3) However subgroups of the elements are formed, each has an effect on the behavior of the whole and none has an independent effect on it." (Russell L Ackoff, "Creating the Corporate Future", 1981) 

"A system is a network of interdependent components that work together to try to accomplish the aim of the system.” (William E Deming, "The New Economics for Industry, Government, Education”, 1993)

"In the most abstract sense, a system is a set of objects together with relationships among the objects. Such a definition implies that a system has properties, functions, and dynamics distinct from its constituent objects and relationships." (Tom R. Burns, "System Theories", 2006) 

"A complex entity that comprises a set of components, along with their properties, relationships and processes, which is described by an equivalent mathematical model." (Evangelos C Papakitsos et al, "The Challenges of Work-Based Learning via Systemic Modelling in the European Union", 2020)

"A group of elements or parts that are organized and interrelated in a pattern of structures that design a specific set of behaviors, often classified as its 'function' or 'purpose'." (Tatiana C Valencia & Stephanie J Valencia, "Cultivating Flow and Happiness in Children", 2020)

"Any notion or physical entity, comprising of mutually interlinked and interacting parts; a set of elements and relationships between them capable of realizing specified objectives; set of elements with specified structure and enabling logically ordered whole, arranged set of statements, views." (Jaroslaw Zelinski, "Synthesis of MOF, MDA, PIM, MVC, and BCE Notations and Patterns", 2020)

🛢DBMS: Query Optimizer (Definitions)

"SQL Server code that analyzes queries and database objects and selects the appropriate query plan. The SQL Server optimizer is a cost-based optimizer. It estimates the cost of each permutation of table accesses in terms of CPU cost and I/O cost." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"A SQL server tool that formulates an optimum execution plan for a query." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"The SQL Server component responsible for generating the optimum execution plan for a query." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"The SQL Server database engine component responsible for generating efficient execution plans for SQL statements." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"A term applied to a process, within a database engine, that attempts to find the fastest method of executing a SQL command against a database." (Gavin Powell, "Beginning Database Design", 2006)

"This is the component in SQL Server that analyzes your queries, compares them with available indexes, and decides which index will return a result set the fastest." (Joseph L Jorden & Dandy Weyn, "MCTS Microsoft SQL Server 2005: Implementation and Maintenance Study Guide - Exam 70-431", 2006)

"An optimization process running within SQL Server. Any queries submitted to SQL Server are first processed by the query optimizer. It determines the best way to run the query, including what indexes to use and what types of joins to use. The output is a query execution plan, sometimes called a query plan or just a plan." (Darril Gibson, "MCITP SQL Server 2005 Database Developer All-in-One Exam Guide", 2008)

"A process that generates query plans. For each query, the optimizer generates a plan that matches the query to the index that will return results as efficiently as possible. The optimizer reuses the query plan each time the query runs. If a collection changes significantly, the optimizer creates a new query plan." (MongoDb, "Glossary", 2008)

"The Optimizer is an internal technology that is responsible for selecting the most efficient means to accessing or altering information. It uses detailed statistics about the database to make the right decision." (Robert D Schneider & Darril Gibson, "Microsoft SQL Server 2008 All-in-One Desk Reference For Dummies", 2008)

"A part of a DBMS that examines a nonprocedural data manipulation request and makes a determination of the most efficient way to process that request." (Jan L Harrington, "SQL Clearly Explained" 3rd Ed., 2010)

"The component of a relational database system responsible for analyzing SQL queries and producing optimal access paths for retrieving data from the database." (Craig S Mullins, "Database Administration", 2012)

"A component of the SQL and XQuery compiler that chooses an access plan for a data manipulation language statement by modeling the execution cost of many alternative access plans and choosing the one with the minimal estimated cost." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

"Built-in database software that determines the most efficient way to execute a SQL statement by considering factors related to the objects referenced and the conditions specified in the statement." (Oracle)

"The MySQL component that determines the best indexes and join order to use for a query, based on characteristics and data distribution of the relevant tables." (MySQL)

🏗️Software Engineering: Components (Just the Quotes)

"With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system." (John Zachman, "A Framework for Information Systems Architecture", 1987)

"Architecture is defined as a clear representation of a conceptual framework of components and their relationships at a point in time […] a discussion of architecture must take into account different levels of architecture. These levels can be illustrated by a pyramid, with the business unit at the top and the delivery system at the base. An enterprise is composed of one or more Business Units that are responsible for a specific business area. The five levels of architecture are Business Unit, Information, Information System, Data and Delivery System. The levels are separate yet interrelated. [...] The idea if an enterprise architecture reflects an awareness that the levels are logically connected and that a depiction at one level assumes or dictates that architectures at the higher level." (W Bradford Rigdon, "Architectures and Standards", 1989)

"Programmers are responsible for software quality - quality in their own work, quality in the products that incorporate their work, and quality at the interfaces between components. Quality has never been and will never be tested in. The responsibility is both moral and professional." (Boris Beizer, "Software Testing Techniques", 1990)

"As the size of software systems increases, the algorithms and data structures of the computation no longer constitute the major design problems. When systems are constructed from many components, the organization of the overall system - the software architecture - presents a new set of design problems. This level of design has been addressed in a number of ways including informal diagrams and descriptive terms, module interconnection languages, templates and frameworks for systems that serve the needs of specific domains, and formal models of component integration mechanisms." (David Garlan & Mary Shaw, "An introduction to software architecture", Advances in software engineering and knowledge engineering Vol 1, 1993)

"Although the concept of an enterprise architecture (EA) has not been well defined and agreed upon, EAs are being developed to support information system development and enterprise reengineering. Most EAs differ in content and nature, and most are incomplete because they represent only data and process aspects of the enterprise. […] An EA is a conceptual framework that describes how an enterprise is constructed by defining its primary components and the relationships among these components." (M A Roos, "Enterprise architecture: definition, content, and utility", Enabling Technologies: Infrastructure for Collaborative Enterprises, 1994)

"An enterprise architecture is an abstract summary of some organizational component's design. The organizational strategy is the basis for deciding where the organization wants to be in three to five years. When matched to the organizational strategy, the architectures provide the foundation for deciding priorities for implementing the strategy." (Sue A Conger, "The new software engineering", 1994)

"Software architecture involves the description of elements from which systems are built, interactions among those elements, patterns that guide their composition, and constraints on these patterns. In general, a particular system is defined in terms of a collection of components and interactions among those components. Such a system may in turn be used as a (composite) element in a larger system design." (Mary Shaw & David Garlan,"Characteristics of Higher-Level Languages for Software Architecture", 1994)

"When the behavior of the system depends on the behavior of the parts, the complexity of the whole must involve a description of the parts, thus it is large. The smaller the parts that must be described to describe the behavior of the whole, the larger the complexity of the entire system. […] A complex system is a system formed out of many components whose behavior is emergent, that is, the behavior of the system cannot be simply inferred from the behavior of its components." (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"Complexity is that property of a model which makes it difficult to formulate its overall behaviour in a given language, even when given reasonably complete information about its atomic components and their inter-relations." (Bruce Edmonds, "Syntactic Measures of Complexity", 1999)

"Enterprise architecture is a family of related architecture components. This include information architecture, organization and business process architecture, and information technology architecture. Each consists of architectural representations, definitions of architecture entities, their relationships, and specification of function and purpose. Enterprise architecture guides the construction and development of business organizations and business processes, and the construction and development of supporting information systems." (Gordon B Davis, "The Blackwell encyclopedic dictionary of management information systems"‎, 1999)

"Enterprise architecture is a holistic representation of all the components of the enterprise and the use of graphics and schemes are used to emphasize all parts of the enterprise, and how they are interrelated. [...] Enterprise architectures are used to deal with intra-organizational processes, interorganizational cooperation and coordination, and their shared use of information and information technologies. Business developments, such as outsourcing, partnership, alliances and Electronic Data Interchange, extend the need for architecture across company boundaries." (Gordon B Davis," The Blackwell encyclopedic dictionary of management information systems"‎, 1999)

"Generically, an architecture is the description of the set of components and the relationships between them. […] A software architecture describes the layout of the software modules and the connections and relationships among them. A hardware architecture can describe how the hardware components are organized. However, both these definitions can apply to a single computer, a single information system, or a family of information systems. Thus 'architecture' can have a range of meanings, goals, and abstraction levels, depending on who’s speaking." (Frank J Armour et al, "A big-picture look at enterprise architectures", IT professional Vol 1 (1), 1999)

"Like a physical model, a conceptual model is an artificial system. It is however, made up of conceptual, and not physical components." (Ibrahim A Halloun, "Modeling Theory in Science Education", 2007) 

"Standards make it easier to reuse ideas and components, recruit people with relevant experience, encapsulate good ideas, and wire components together. However, the process of creating standards can sometimes take too long for industry to wait, and some standards lose touch with the real needs of the adopters they are intended to serve." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"Taking a systems approach means paying close attention to results, the reasons we build a system. Architecture must be grounded in the client’s/user’s/customer’s purpose. Architecture is not just about the structure of components. One of the essential distinguishing features of architectural design versus other sorts of engineering design is the degree to which architectural design embraces results from the perspective of the client/user/customer. The architect does not assume some particular problem formulation, as 'requirements' is fixed. The architect engages in joint exploration, ideally directly with the client/user/customer, of what system attributes will yield results worth paying for."  (Mark W Maier, "The Art Systems of Architecting" 3rd Ed., 2009)

"In many applications, integration or functional tests are used by default as the standard way to test almost all aspects of the system. However integration and functional tests are not the best way to detect and identify bugs. Because of the large number of components involved in a typical end-to-end test, it can be very hard to know where something has gone wrong. In addition, with so many moving parts, it is extremely difficult, if not completely unfeasible, to cover all of the possible paths through the application." (John F Smart, "Jenkins: The Definitive Guide", 2011)

"Programming is a personal activity and there is no general process that is usually followed. Some programmers start with components that they understand, develop these, and then move on to less-understood components. Others take the opposite approach, leaving familiar components till last because they know how to develop them. Some developers like to define data early in the process then use this to drive the program development; others leave data unspecified for as long as possible." (Ian Sommerville, "Software Engineering" 9th Ed., 2011)

🌁Software Engineering: Black Box (Definitions)

"Objects or chunks of code that can function independently, where changes made to one part of a piece of software will not affect others." (Gavin Powell, "Beginning Database Design", 2006)

"A component or device with an input and an output, whose inner workings need not be understood by or accessible to the user." (Judith Hurwitz et al, "Service Oriented Architecture For Dummies" 2nd Ed., 2009)

"A risk model that lacks transparency of its specific risk assumptions, measures, and findings. These models sometimes create as many risks for the organization as they are meant to manage." (Annetta Cortez & Bob Yehling, "The Complete Idiot's Guide® To Risk Management", 2010)

"A component or device with an input and an output whose inner workings need not be understood by or accessible to the user." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"Is a metaphor describing how people are unable to see or understand how technologies work and is particularly used to characterize the lack of understanding of how an algorithm works. While we can understand the outputs of artificial intelligence (AI) - in terms of recommendations, decisions and so on - the processes to achieve them are too complicated for us to understand. Concerns about the black box nature of AI center on its apparent lack of accountability, potential unseen biases and the inability to have clear visibility into what is driving an AI’s potentially life-changing decisions." (Accenture)

🌁Software Engineering: Fault Tolerance (Definitions)

"A property of neural computing systems that allows the system to function and gradually degrade when a small number of processing elements are destroyed or disabled." (Guido Deboeck & Teuvo Kohonen (Eds), "Visual Explorations in Finance with Self-Organizing Maps" 2nd Ed., 2000)

"Fault Tolerance is the ability of an IT system to continue to function as designed even though a fault has occurred." (Martin Oberhofer et al, "Enterprise Master Data Management", 2008)

"The ability of a system to provide an uninterrupted service, despite the failure of one or more of the system’s components." (Judith Hurwitz et al, "Service Oriented Architecture For Dummies" 2nd Ed., 2009)

"The ability of a system or component to continue normal operation despite the presence of hardware or software faults." (Mark S Merkow & Lakshmikanth Raghavan, "Secure and Resilient Software Development", 2010)

"The capability of a system to provide uninterrupted service despite the failure of one or more of the system’s components." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"1. The capability of the software product or a component to maintain a specified level of performance in case of wrong inputs (see also robustness). 2. The capability of the software product or a component to maintain a specified level of performance in case of software faults (defects) or of infringement of its specified interface." (Tilo Linz et al, "Software Testing Foundations" 4th Ed., 2014)

"The ability of a system to tolerate a fault and continue to operate. Fault tolerance systems often use redundant hardware, such as additional hard drives or additional servers, to eliminate a single point of failure." (Darril Gibson, "Effective Help Desk Specialist Skills", 2014)

"Ability to continue operate after failure of a component part" (ITIL)

"The capability of the software product to maintain a specified level of performance in cases of software faults (defects) or of infringement of its specified interface." (ISO 9126)

🌁Software Engineering: Failure (Definitions)

"[...] a fault is a potential failure, which can cause an incorrect result (failure) in the future, or may have already caused one. The failure may not have observable consequences, however, and so may not be reported as a problem." (Richard D Stutzke, "Estimating Software-Intensive Systems: Projects, Products, and Processes", 2005)

"1. Deviation of the component or system from its expected delivery, service, or result. (For a test result, the observed result and the expected [specified or predicted] result do not match.) 2. Result of a fault that, during test execution, shows an externally observable wrong result. 3. Behavior of a test object that does not conform to a specified functionality that should be suitable for its use." (Tilo Linz et al, "Software Testing Foundations, 4th Ed", 2014)

"The condition of not achieving the desired end results." (Ken Sylvester, "Negotiating in the Leadership Zone", 2015)

"A system failure is an event that occurs when the delivered service deviates from correct service (implementing system function). A system may fail either because it does not comply with the specification or because the specification did not adequately describe its function." (O Sami Saydjari, "Engineering Trustworthy Systems: Get Cybersecurity Design Right the First Time", 2018)

"Deviation of the component or system from its expected delivery, service or result." (Software Quality Assurance)

"Loss of ability to operate to specification, or to deliver required output" (ITIL)

"The inability of a system or component to perform its required functions within specified performance requirements. The fault tolerance discipline distinguishes between a human action (a mistake), its manifestation (a hardware or software fault), the result of the fault (a failure), and the amount by which the results are incorrect (the error)." (IEEE Std 610.12-1990) 

🌁Software Engineering: Middleware (Definitions)

"An intermediate layer that may consist of either hardware or software that facilitates interaction across dissimilar hardware and network environments." (Microsoft Corporation, "Microsoft SQL Server 7.0 Data Warehouse Training Kit", 2000)

"A general term for any software that allows two separate and usually already existing programs to exchange data without the need for custom coding." (Richard D Stutzke, "Estimating Software-Intensive Systems: Projects, Products, and Processes", 2005)

"Multipurpose software that lives at a layer between the operating system and application in distributed computing environments." (Judith Hurwitz et al, "Service Oriented Architecture For Dummies" 2nd Ed., 2009)

"Computer software or hardware that connects other software components or systems. This technology evolved to provide for interoperability in support of the move to coherent distributed architectures, which are used most often to support complex distributed applications. It includes Web servers, application servers, and similar tools that support application development and delivery. Middleware is especially integral in managing and optimizing a system-of-systems at the enterprise level. Middleware sits “in the middle” between applications that may be working on different operating systems. It is similar to the middle layer of a three-tier single-system architecture, except that it is stretched across multiple systems or applications. " (David Lyle & John G Schmidt, "Lean Integration", 2010)

"Software that connects software components or applications, functioning as a conversion or translation layer or a consolidator and integrator. Middleware enables one application to communicate with another that runs on a different platform or comes from a different vendor, and it allows multiple processes running on one or more machines to interact across a network." (Janice M Roehl-Anderson, "IT Best Practices for Financial Managers", 2010)

"The term refers to software services that are placed between applications and database servers to make the data interchange transparent and efficient." (Paulraj Ponniah, "Data Warehousing Fundamentals for IT Professionals", 2010)

"Software that allows applications to interact across hardware and network environments." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"software that connects other software." (Bill Holtsnider & Brian D Jaffe, "IT Manager's Handbook" 3rd Ed., 2012)

"Software that connects two otherwise separate applications." (Craig S Mullins, "Database Administration", 2012)

"Software that sits between two or more types of software and translates information between them. Middleware can cover a broad spectrum of software and generally sits between an application and an operating system, a network operating system, or a database management system." (Microsoft, "SQL Server 2012 Glossary", 2012)