26 December 2013

Project Management: Laws (Just the Quotes)

"Nothing will ever be attempted if all possible objections must first be overcome." (Samuel Johnson, 1759)

"In anything at all, perfection is finally attained not when there is no longer anything to add, but when there is no longer anything to take away [...]" (Antoine de Saint Exupéry, "Wind, Sand and Stars", 1939) 

"Work expands so as to fill the time available for its completion." (C Northcote Parkinson, "Parkinson’s Law", 1957) 

"Adding manpower to a late software project makes it later." (Fred Brooks, "The Mythical Man-Month", 1975)

"By failing to plan, you will free very little, if any, time, and by failing to plan you will almost certainly fail […] Exactly because we lack time to plan, we should take time to plan." (Alan Lakein, "How to get control of your time and your life", 1974) 

"Program advocates like to keep bad news covered up until they have spent so much money they can advance the sunk-cost argument; that it's too late to cancel the program because we've spent too much already." (James P Stevenson, "The Pentagon Paradox: The development of the F-18 Hornet", 1993)

Graham's Law: "If they know nothing of what you are doing, they suspect you are doing nothing." (Robert J Graham et al, "The Complete Idiot's Guide to Project Management", 2007) 

O'Brochta's Law: "Project management is about applying common sense with uncommon discipline." (Michael O'Brochta, "Great Project Managers", 2008) 

"No project should be allowed to proceed without clear specification and acceptance  criteria, that are understood by all participants." (Tony Martyr, "Why Projects Fail", 2018)

Augustine's Law: "A bad idea executed to perfection is still a bad idea." (Norman R Augustine)

Cohn's Law: "The more time you spend in reporting on what you are doing, the less time you have to do anything. Stability is achieved when you spend all your time doing nothing but reporting on the nothing you are doing."

Fitzgerald's Law: "There are two states to any large project: Too early to tell and too late to stop." (Ernest Fitzgerald)

Hoggarth's Law: "Attempts to get answers early in a project fail as there are many more wrong questions than right ones. Activity during the early stages should be dedicated to finding the correct questions. Once the correct questions have been identified correct answers will naturally fall out of subsequent work without grief or excitement and there will be understanding of what the project is meant to achieve."

Kinser's Law: "About the time you finish doing something, you know enough to start." (James C Kinser) 

Operations Management: Operations Research (Just the Quotes)

"No science has ever been born on a specific day. Each science emerges out of a convergence of an increased interest in some class of problems and the development of scientific methods, techniques, and tools which are adequate to solve these problems. Operations Research (O. R.) is no exception. Its roots are as old as science and the management function." (C West Churchman et al., "Introduction to Operations Research", 1957)

"An objective of O.R. as it emerged from this evolution of industrial organization, is to provide managers of the organizations with a scientific basis for solving problems involving the interaction of the components of the organization in the best interest of the organization as a whole. A decision which is best for the organization as a whole is called optimum decision." (C West Churchman et al, "Introduction to Operations Research", 1957) 

"The systems approach to problems does not mean that the most generally formulated problem must be solved in one research project. However desirable this may be, it is seldom possible to realize it in practice. In practice, parts of the total problem are usually solved in sequence. In many cases the total problem cannot be formulated in advance but the solution of one phase of it helps define the next phase. For example, a production control project may require determination of the most economic production quantities of different items. Once these are found it may turn out that these quantities cannot be produced on the available equipment in the available time. This, then, gives rise to a new problem whose solution will affect the solution obtained in the first phase." (C West Churchman et al, "Introduction to Operations Research", 1957) 

"The concern of OR with finding an optimum decision, policy, or design is one of its essential characteristics. It does not seek merely to define a better solution to a problem than the one in use; it seeks the best solution... [It] can be characterized as the application of scientific methods, techniques, and tools to problems involving the operations of systems so as to provide those in control of the operations with optimum solutions to the problems." (C West Churchman et al, "Introduction to Operations Research", 1957) 

"Operational research is the application of methods of the research scientist to various rather complex practical operations." (John F T Hassell, "The Scientific Approach", 1965) 

"Operations research (OR) is the securing of improvement in social systems by means of scientific method." (C West Churchman, "Operations research as a profession", 1970)

"Decision theory, as it has grown up in recent years, is a formalization of the problems involved in making optimal choices. In a certain sense - a very abstract sense, to be sure - it incorporates among others operations research, theoretical economics, and wide areas of statistics, among others." (Kenneth Arrow, "The Economics of Information", 1984) 

"The lag between knowing the facts and knowing the system which generates the facts can be considerable. […] Similarly there is a lag in passing from the stage in which sets of empirical observations constitute exciting discoveries, to the stage of insight into underlying mechanism, in every field of management today. In controlling the economy and diplomacy and society at large, in controlling business and industry and commerce, we have collected facts and perhaps identified systems. But we have barely begun to explain their underlying mechanism. This is what operational research is for." (Stanford Beer, "Decision and Control", 1994)

24 December 2013

Knowledge Management: Knowledge (Just the Quotes)

"There are two modes of acquiring knowledge, namely, by reasoning and experience. Reasoning draws a conclusion and makes us grant the conclusion, but does not make the conclusion certain, nor does it remove doubt so that the mind may rest on the intuition of truth unless the mind discovers it by the path of experience." (Roger Bacon, "Opus Majus", 1267)

"Knowledge being to be had only of visible and certain truth, error is not a fault of our knowledge, but a mistake of our judgment, giving assent to that which is not true." (John Locke, "An Essay Concerning Human Understanding", 1689)

"[…] the highest probability amounts not to certainty, without which there can be no true knowledge." (John Locke, "An Essay Concerning Human Understanding", 1689)

"It is your opinion, the ideas we perceive by our senses are not real things, but images, or copies of them. Our knowledge therefore is no farther real, than as our ideas are the true representations of those originals. But as these supposed originals are in themselves unknown, it is impossible to know how far our ideas resemble them; or whether they resemble them at all. We cannot therefore be sure we have any real knowledge." (George Berkeley, "Three Dialogues", 1713)

"Our knowledge springs from two fundamental sources of the mind; the first is the capacity of receiving representations (receptivity for impressions), the second is the power of knowing an object through these representations (spontaneity [in the production] of concepts)." (Immanuel Kant, "Critique of Pure Reason", 1781)

"Knowledge is only real and can only be set forth fully in the form of science, in the form of system." (G W Friedrich Hegel, "The Phenomenology of Mind", 1807)

"One may even say, strictly speaking, that almost all our knowledge is only probable; and in the small number of things that we are able to know with certainty, in the mathematical sciences themselves, the principal means of arriving at the truth - induction and analogy - are based on probabilities, so that the whole system of human knowledge is tied up with the theory set out in this essay." (Pierre-Simon Laplace, "Philosophical Essay on Probabilities", 1814) 

"We [...] are profiting not only by the knowledge, but also by the ignorance, not only by the discoveries, but also by the errors of our forefathers; for the march of science, like that of time, has been progressing in the darkness, no less than in the light." (Charles C Colton, "Lacon", 1820)

"Our knowledge of circumstances has increased, but our uncertainty, instead of having diminished, has only increased. The reason of this is, that we do not gain all our experience at once, but by degrees; so our determinations continue to be assailed incessantly by fresh experience; and the mind, if we may use the expression, must always be under arms." (Carl von Clausewitz, "On War", 1832)

"All knowledge is profitable; profitable in its ennobling effect on the character, in the pleasure it imparts in its acquisition, as well as in the power it gives over the operations of mind and of matter. All knowledge is useful; every part of this complex system of nature is connected with every other. Nothing is isolated. The discovery of to-day, which appears unconnected with any useful process, may, in the course of a few years, become the fruitful source of a thousand inventions." (Joseph Henry, "Report of the Secretary" [Sixth Annual Report of the Board of Regents of the Smithsonian Institution for 1851], 1852)

"Isolated facts and experiments have in themselves no value, however great their number may be. They only become valuable in a theoretical or practical point of view when they make us acquainted with the law of a series of uniformly recurring phenomena, or, it may be, only give a negative result showing an incompleteness in our knowledge of such a law, till then held to be perfect." (Hermann von Helmholtz, "The Aim and Progress of Physical Science", 1869)

"Simplification of modes of proof is not merely an indication of advance in our knowledge of a subject, but is also the surest guarantee of readiness for farther progress." (William T Kelvin, "Elements of Natural Philosophy", 1873)

"The whole value of science consists in the power which it confers upon us of applying to one object the knowledge acquired from like objects; and it is only so far, therefore, as we can discover and register resemblances that we can turn our observations to account." (William S Jevons, "The Principles of Science: A Treatise on Logic and Scientific Method", 1874)

"[…] when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely in your thoughts advanced to the state of science." (William T Kelvin, "Electrical Units of Measurement", 1883)

"The smallest group of facts, if properly classified and logically dealt with, will form a stone which has its proper place in the great building of knowledge, wholly independent of the individual workman who has shaped it." (Karl Pearson, "The Grammar of Science", 1892)

"Without a theory all our knowledge of nature would be reduced to a mere inventory of the results of observation. Every scientific theory must be regarded as an effort of the human mind to grasp the truth, and as long as it is consistent with the facts, it forms a chain by which they are linked together and woven into harmony." (Thomas Preston, "The Theory of Heat", 1894)

"Knowledge is the distilled essence of our intuitions, corroborated by experience." (Elbert Hubbard, "A Thousand & One Epigrams, 1911)

"It is experience which has given us our first real knowledge of Nature and her laws. It is experience, in the shape of observation and experiment, which has given us the raw material out of which hypothesis and inference have slowly elaborated that richer conception of the material world which constitutes perhaps the chief, and certainly the most characteristic, glory of the modern mind." (Arthur J Balfour, "The Foundations of Belief", 1912)

"We have discovered that it is actually an aid in the search for knowledge to understand the nature of the knowledge we seek." (Arthur S Eddington, "The Philosophy of Physical Science", 1938)

"Science usually advances by a succession of small steps, through a fog in which even the most keen-sighted explorer can seldom see more than a few paces ahead. Occasionally the fog lifts, an eminence is gained, and a wider stretch of territory can be surveyed - sometimes with startling results. A whole science may then seem to undergo a kaleidoscopic ‘rearrangement’, fragments of knowledge being found to fit together in a hitherto unsuspected manner. Sometimes the shock of readjustment may spread to other sciences; sometimes it may divert the whole current of human thought." (James H Jeans, "Physics and Philosophy" 3rd Ed., 1943)

"Every bit of knowledge we gain and every conclusion we draw about the universe or about any part or feature of it depends finally upon some observation or measurement. Mankind has had again and again the humiliating experience of trusting to intuitive, apparently logical conclusions without observations, and has seen Nature sail by in her radiant chariot of gold in an entirely different direction." (Oliver J Lee, "Measuring Our Universe: From the Inner Atom to Outer Space", 1950)

"The essence of knowledge is generalization. That fire can be produced by rubbing wood in a certain way is a knowledge derived by generalization from individual experiences; the statement means that rubbing wood in this way will always produce fire. The art of discovery is therefore the art of correct generalization." (Hans Reichenbach, "The Rise of Scientific Philosophy", 1951)

"Knowledge rests on knowledge; what is new is meaningful because it departs slightly from what was known before; this is a world of frontiers, where even the liveliest of actors or observers will be absent most of the time from most of them." (J Robert Oppenheimer, "Science and the Common Understanding", 1954)

"Knowledge is not something which exists and grows in the abstract. It is a function of human organisms and of social organization. Knowledge, that is to say, is always what somebody knows: the most perfect transcript of knowledge in writing is not knowledge if nobody knows it. Knowledge however grows by the receipt of meaningful information - that is, by the intake of messages by a knower which are capable of reorganising his knowledge." (Kenneth E Boulding, "General Systems Theory - The Skeleton of Science", Management Science Vol. 2 (3), 1956)

"Incomplete knowledge must be considered as perfectly normal in probability theory; we might even say that, if we knew all the circumstances of a phenomenon, there would be no place for probability, and we would know the outcome with certainty." (Félix E Borel, Probability and Certainty", 1963)

"Knowing reality means constructing systems of transformations that correspond, more or less adequately, to reality. They are more or less isomorphic to transformations of reality. The transformational structures of which knowledge consists are not copies of the transformations in reality; they are simply possible isomorphic models among which experience can enable us to choose. Knowledge, then, is a system of transformations that become progressively adequate." (Jean Piaget, "Genetic Epistemology", 1968)

"Scientific knowledge is not created solely by the piecemeal mining of discrete facts by uniformly accurate and reliable individual scientific investigations. The process of criticism and evaluation, of analysis and synthesis, are essential to the whole system. It is impossible for each one of us to be continually aware of all that is going on around us, so that we can immediately decide the significance of every new paper that is published. The job of making such judgments must therefore be delegated to the best and wisest among us, who speak, not with their own personal voices, but on behalf of the whole community of Science. […] It is impossible for the consensus - public knowledge - to be voiced at all, unless it is channeled through the minds of selected persons, and restated in their words for all to hear." (John M Ziman, "Public Knowledge: An Essay Concerning the Social Dimension of Science", 1968)

"Models constitute a framework or a skeleton and the flesh and blood will have to be added by a lot of common sense and knowledge of details."(Jan Tinbergen, "The Use of Models: Experience," 1969)

"Human knowledge is personal and responsible, an unending adventure at the edge of uncertainty." (Jacob Bronowski, "The Ascent of Man", 1973)

"Knowledge is not a series of self-consistent theories that converges toward an ideal view; it is rather an ever increasing ocean of mutually incompatible (and perhaps even incommensurable) alternatives, each single theory, each fairy tale, each myth that is part of the collection forcing the others into greater articulation and all of them contributing, via this process of competition, to the development of our consciousness." (Paul K Feyerabend, "Against Method: Outline of an Anarchistic Theory of Knowledge", 1975)

"Knowledge is the appropriate collection of information, such that it's intent is to be useful. Knowledge is a deterministic process. When someone 'memorizes' information (as less-aspiring test-bound students often do), then they have amassed knowledge. This knowledge has useful meaning to them, but it does not provide for, in and of itself, an integration such as would infer further knowledge." (Russell L Ackoff, "Towards a Systems Theory of Organization", 1985)

"There is no coherent knowledge, i.e. no uniform comprehensive account of the world and the events in it. There is no comprehensive truth that goes beyond an enumeration of details, but there are many pieces of information, obtained in different ways from different sources and collected for the benefit of the curious. The best way of presenting such knowledge is the list - and the oldest scientific works were indeed lists of facts, parts, coincidences, problems in several specialized domains." (Paul K Feyerabend, "Farewell to Reason", 1987)

"We admit knowledge whenever we observe an effective (or adequate) behavior in a given context, i.e., in a realm or domain which we define by a question (explicit or implicit)." (Humberto Maturana & Francisco J Varela, "The Tree of Knowledge", 1987)

"We live on an island surrounded by a sea of ignorance. As our island of knowledge grows, so does the shore of our ignorance." (John A Wheeler, Scientific American Vol. 267, 1992)

"Knowledge is theory. We should be thankful if action of management is based on theory. Knowledge has temporal spread. Information is not knowledge. The world is drowning in information but is slow in acquisition of knowledge. There is no substitute for knowledge." (William E Deming, "The New Economics for Industry, Government, Education", 1993) 

"Discourses are ways of referring to or constructing knowledge about a particular topic of practice: a cluster (or formation) of ideas, images and practices, which provide ways of talking about, forms of knowledge and conduct associated with, a particular topic, social activity or institutional site in society. These discursive formations, as they are known, define what is and is not appropriate in our formulation of, and our practices in relation to, a particular subject or site of social activity." (Stuart Hall, "Representation: Cultural Representations and Signifying Practices", 1997)

"An individual understands a concept, skill, theory, or domain of knowledge to the extent that he or she can apply it appropriately in a new situation." (Howard Gardner, "The Disciplined Mind", 1999)

"Knowledge is factual when evidence supports it and we have great confidence in its accuracy. What we call 'hard fact' is information supported by  strong, convincing evidence; this means evidence that, so far as we know, we cannot deny, however we examine or test it. Facts always can be questioned, but they hold up under questioning. How did people come by this information? How did they interpret it? Are other interpretations possible? The more satisfactory the answers to such questions, the 'harder' the facts." (Joel Best, Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists, 2001)

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

21 December 2013

Knowledge Management: Information Overload (Just the Quotes)

"Every person seems to have a limited capacity to assimilate information, and if it is presented to him too rapidly and without adequate repetition, this capacity will be exceeded and communication will break down." (R Duncan Luce, "Developments in Mathematical Psychology", 1960)

"Information overload occurs when the amount of input to a system exceeds its processing capacity. Decision makers have fairly limited cognitive processing capacity. Consequently, when information overload occurs, it is likely that a reduction in decision quality will occur." (Bertram Gross, "The Managing of Organizations", 1964)

"My experience indicates that most managers receive much more data (if not information) than they can possibly absorb even if they spend all of their time trying to do so. Hence they already suffer from an information overload." (Russell L Ackoff, "Management misinformation systems", 1967)

"One of the effects of living with electric information is that we live habitually in a state of information overload. There's always more than you can cope with." (Marshall McLuhan, "The Best of Ideas", 1967)

"Unless the information overload to which managers are subjected is reduced, any additional information made available by an MIS cannot be expected to be used effectively." (Russell L Ackoff, "Management misinformation systems", 1967)

"People today are in danger of drowning in information; but, because they have been taught that information is useful, they are more willing to drown than they need be. If they could handle information, they would not have to drown at all." (Idries Shah, "Reflections", 1968)

"Faced with information overload, we have no alternative but pattern-recognition."(Marshall McLuhan, "Counterblast", 1969)

"We live in and age of hyper-awareness, our senses extend around the globe, but it's the case of aesthetic overload: our technical zeal has outstripped our psychic capacity to cope with the influx of information." (Gene Youngblood, "Expanded Cinema", 1970)

"[...] in an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it." (Herbert Simon, "Designing Organizations for an Information-Rich World", 1971)

"Everyone spoke of an information overload, but what there was in fact was a non-information overload." (Richard S Wurman, "What-If, Could-Be", 1976)

"The greater the uncertainty, the greater the amount of decision making and information processing. It is hypothesized that organizations have limited capacities to process information and adopt different organizing modes to deal with task uncertainty. Therefore, variations in organizing modes are actually variations in the capacity of organizations to process information and make decisions about events which cannot be anticipated in advance." (John K Galbraith, "Organization Design", 1977)

"We are drowning in information but starved for knowledge." (John Naisbitt, "Megatrends: Ten New Directions Transforming Our Lives", 1982)

"In the Information Age, the first step to sanity is FILTERING. Filter the information: extract for knowledge. Filter first for substance. Filter second for significance. […] Filter third for reliability. […] Filter fourth for completeness." (Marc Stiegler, "David’s Sling", 1988)

"Intuition becomes increasingly valuable in the new information society precisely because there is so much data." (John Naisbit, "Re-Inventing the Corporation", 1988)

"What about confusing clutter? Information overload? Doesn't data have to be ‘boiled down’ and  ‘simplified’? These common questions miss the point, for the quantity of detail is an issue completely separate from the difficulty of reading. Clutter and confusion are failures of design, not attributes of information." (Edward R Tufte, "Envisioning Information", 1990)

"Traditional ways to deal with information - reading, listening, writing, talking - are painfully slow in comparison to 'viewing the big picture'. Those who survive information overload will be those who search for information with broadband thinking but apply it with a single-minded focus." (Kathryn Alesandrini, "Survive Information Overload: The 7 Best Ways to Manage Your Workload by Seeing the Big Picture", 1992)

"'Point of view' is that quintessentially human solution to information overload, an intuitive process of reducing things to an essential relevant and manageable minimum. [...] In a world of hyperabundant content, point of view will become the scarcest of resources." (Paul Saffo, "It's The Context, Stupid", 1994) 

"We live in a world where there is more and more information, and less and less meaning." (Jean Baudrillard, "Simulacra and simulation", 1994)

"Specialization, once a maneuver methodically to collect information, now is a manifestation of information overloads. The role of information has changed. Once justified as a means of comprehending the world, it now generates a conflicting and contradictory, fleeting and fragmentation field of disconnected and undigested data." (Stelarc, From Psycho-Body to Cyber-Systems: Images as Post-human Entities, 1998)

"We all would like to know more and, at the same time, to receive less information. In fact, the problem of a worker in today's knowledge industry is not the scarcity of information but its excess. The same holds for professionals: just think of a physician or an executive, constantly bombarded by information that is at best irrelevant. In order to learn anything we need time. And to make time we must use information filters allowing us to ignore most of the information aimed at us. We must ignore much to learn a little." (Mario Bunge, "Philosophy in Crisis: The Need for Reconstruction", 2001)

"One of the effects of living with electric information is that we live habitually in a state of information overload. There's always more than you can cope with." (Marshall McLuhan, "Understanding Me: Lectures and Interviews" , 2003)

"What’s next for technology and design? A lot less thinking about technology for technology’s sake, and a lot more thinking about design. Art humanizes technology and makes it understandable. Design is needed to make sense of information overload. It is why art and design will rise in importance during this century as we try to make sense of all the possibilities that digital technology now affords." (John Maeda, "Why Apple Leads the Way in Design", 2010) 

"The instinctual shortcut that we take when we have 'too much information' is to engage with it selectively, picking out the parts we like and ignoring the remainder, making allies with those who have made the same choices and enemies of the rest." (Nate Silver, "The Signal and the Noise", 2012)

"Complexity has the propensity to overload systems, making the relevance of a particular piece of information not statistically significant. And when an array of mind-numbing factors is added into the equation, theory and models rarely conform to reality." (Lawrence K Samuels, "Defense of Chaos: The Chaology of Politics, Economics and Human Action", 2013)

"In this time of 'information overload', people do not need more information. They want a story they can relate to." (Maarten Schafer, "Around the World in 80 Brands", 2014)

"Today, technology has lowered the barrier for others to share their opinion about what we should be focusing on. It is not just information overload; it is opinion overload." (Greg McKeown, "Essentialism: The Disciplined Pursuit of Less", 2014)

"There is so much information that our ability to focus on any piece of it is interrupted by other information, so that we bathe in information but hardly absorb or analyse it. Data are interrupted by other data before we've thought about the first round, and contemplating three streams of data at once may be a way to think about none of them." (Rebecca Solnit, "The Encyclopedia of Trouble and Spaciousness", 2014) 

"While having information is a crucial first step, more information isn't necessarily better. Take a look at your bookshelves and the list of seminars you have attended. If you have read more than one book about a subject or attended more than one seminar but still haven’t reached your goals, then your problem is not lack of information but rather lack of implementation." (Gudjon Bergmann)

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

16 December 2013

Knowledge Management: Data, Information, Knowledge, Wisdom (Just the Quotes)

 "Knowledge is of two kinds. We know a subject ourselves, or we know where we can find information upon it." (Samuel Johnson, 1775)

"It is almost as difficult to make a man unlearn his errors as his knowledge. Mal-information is more hopeless than non-information; for error is always more busy than ignorance. Ignorance is a blank sheet, on which we may write; but error is a scribbled one, on which we must first erase. Ignorance is contented to stand still with her back to the truth; but error is more presumptuous, and proceeds in the same direction. Ignorance has no light, but error follows a false one. The consequence is, that error, when she retraces her footsteps, has further to go, before she can arrive at the truth, than ignorance." (Charles C Colton, “Lacon”, 1820)

"In every branch of knowledge the progress is proportional to the amount of facts on which to build, and therefore to the facility of obtaining data." (James C Maxwell, [Letter to Lewis Campbell] 1851) 

"[The information of a message can] be defined as the 'minimum number of binary decisions which enable the receiver to construct the message, on the basis of the data already available to him.' These data comprise both the convention regarding the symbols and the language used, and the knowledge available at the moment when the message started." (Dennis Gabor, "Optical transmission" in Information Theory : Papers Read at a Symposium on Information Theory, 1952)

"Knowledge is not something which exists and grows in the abstract. It is a function of human organisms and of social organization. Knowledge, that is to say, is always what somebody knows: the most perfect transcript of knowledge in writing is not knowledge if nobody knows it. Knowledge however grows by the receipt of meaningful information - that is, by the intake of messages by a knower which are capable of reorganising his knowledge." (Kenneth E Boulding, "General Systems Theory - The Skeleton of Science", Management Science Vol. 2 (3), 1956)

"The idea of knowledge as an improbable structure is still a good place to start. Knowledge, however, has a dimension which goes beyond that of mere information or improbability. This is a dimension of significance which is very hard to reduce to quantitative form. Two knowledge structures might be equally improbable but one might be much more significant than the other." (Kenneth E Boulding, "Beyond Economics: Essays on Society", 1968)

"In perception itself, two distinct processes can be discerned. One is the gathering of the primary, sensory data or simple sensing of such things as light, moisture or pressure, and the other is the structuring of such data into information." (Edward Ihnatowicz, "The Relevance of Manipulation to the Process of Perception", 1977) 

"Data, seeming facts, apparent asso­ciations-these are not certain knowledge of something. They may be puzzles that can one day be explained; they may be trivia that need not be explained at all. (Kenneth Waltz, "Theory of International Politics", 1979)

"Knowledge is the appropriate collection of information, such that it's intent is to be useful. Knowledge is a deterministic process. When someone 'memorizes' information (as less-aspiring test-bound students often do), then they have amassed knowledge. This knowledge has useful meaning to them, but it does not provide for, in and of itself, an integration such as would infer further knowledge." (Russell L Ackoff, "Towards a Systems Theory of Organization", 1985)

"Information is data that has been given meaning by way of relational connection. This 'meaning' can be useful, but does not have to be. In computer parlance, a relational database makes information from the data stored within it." (Russell L Ackoff, "Towards a Systems Theory of Organization", 1985)

"There is no coherent knowledge, i.e. no uniform comprehensive account of the world and the events in it. There is no comprehensive truth that goes beyond an enumeration of details, but there are many pieces of information, obtained in different ways from different sources and collected for the benefit of the curious. The best way of presenting such knowledge is the list - and the oldest scientific works were indeed lists of facts, parts, coincidences, problems in several specialized domains." (Paul K Feyerabend, "Farewell to Reason", 1987) 

"Probabilities are summaries of knowledge that is left behind when information is transferred to a higher level of abstraction." (Judea Pearl, "Probabilistic Reasoning in Intelligent Systems: Network of Plausible, Inference", 1988)

"Information engineering has been defined with the reference to automated techniques as follows: An interlocking set of automated techniques in which enterprise models, data models and process models are built up in a comprehensive knowledge-base and are used to create and maintain data-processing systems." (James Martin, "Information Engineering, 1989)

"Knowledge is theory. We should be thankful if action of management is based on theory. Knowledge has temporal spread. Information is not knowledge. The world is drowning in information but is slow in acquisition of knowledge. There is no substitute for knowledge." (William E Deming, "The New Economics for Industry, Government, Education", 1993)

"Knowledge, truth, and information flow in networks and swarm systems. I have always been interested in the texture of scientific knowledge because it appears to be lumpy and uneven. Much of what we collectively know derives from a few small areas, yet between them lie vast deserts of ignorance. I can interpret that observation now as the effect of positive feedback and attractors. A little bit of knowledge illuminates much around it, and that new illumination feeds on itself, so one corner explodes. The reverse also holds true: ignorance breeds ignorance. Areas where nothing is known, everyone avoids, so nothing is discovered. The result is an uneven landscape of empty know-nothing interrupted by hills of self-organized knowledge." (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995) 

"Now that knowledge is taking the place of capital as the driving force in organizations worldwide, it is all too easy to confuse data with knowledge and information technology with information." (Peter Drucker, "Managing in a Time of Great Change", 1995)

"Data is discrimination between physical states of things (black, white, etc.) that may convey or not convey information to an agent. Whether it does so or not depends on the agent's prior stock of knowledge." (Max Boisot, "Knowledge Assets", 1998)

"The unit of coding is the most basic segment, or element, of the raw data or information that can be assessed in a meaningful way regarding the phenomenon." (Richard Boyatzis, "Transforming qualitative information", 1998)

"While hard data may inform the intellect, it is largely soft data that generates wisdom." (Henry Mintzberg, "Strategy Safari: A Guided Tour Through The Wilds of Strategic Management", 1998)

"Information is just bits of data. Knowledge is putting them together. Wisdom is transcending them." (Ram Dass, "One-Liners: A Mini-Manual for a Spiritual Life (ed. Harmony", 2007)

"Traditional statistics is strong in devising ways of describing data and inferring distributional parameters from sample. Causal inference requires two additional ingredients: a science-friendly language for articulating causal knowledge, and a mathematical machinery for processing that knowledge, combining it with data and drawing new causal conclusions about a phenomenon."(Judea Pearl, "Causal inference in statistics: An overview", Statistics Surveys 3, 2009)

"We also use our imagination and take shortcuts to fill gaps in patterns of nonvisual data. As with visual input, we draw conclusions and make judgments based on uncertain and incomplete information, and we conclude, when we are done analyzing the patterns, that out picture is clear and accurate. But is it?" (Leonard Mlodinow, "The Drunkard's Walk: How Randomness Rules Our Lives", 2009) 

"We reach wisdom when we achieve a deep understanding of acquired knowledge, when we not only 'get it', but when new information blends with prior experience so completely that it makes us better at knowing what to do in other situations, even if they are only loosely related to the information from which our original knowledge came. Just as not all the information we absorb leads to knowledge, not all of the knowledge we acquire leads to wisdom." (Alberto Cairo, "The Functional Art", 2011)

"Any knowledge incapable of being revised with advances in data and human thinking does not deserve the name of knowledge." (Jerry Coyne, "Faith Versus Fact", 2015)

"The term data, unlike the related terms facts and evidence, does not connote truth. Data is descriptive, but data can be erroneous. We tend to distinguish data from information. Data is a primitive or atomic state (as in ‘raw data’). It becomes information only when it is presented in context, in a way that informs. This progression from data to information is not the only direction in which the relationship flows, however; information can also be broken down into pieces, stripped of context, and stored as data. This is the case with most of the data that’s stored in computer systems. Data that’s collected and stored directly by machines, such as sensors, becomes information only when it’s reconnected to its context."  (Stephen Few, "Signal: Understanding What Matters in a World of Noise", 2015)

"Real wisdom is not the knowledge of everything, but the knowledge of which things in life are necessary, which are less necessary, and which are completely unnecessary to know." (Lev N Tolstoy)

"The Information Age offers much to mankind, and I would like to think that we will rise to the challenges it presents. But it is vital to remember that information - in the sense of raw data - is not knowledge, that knowledge is not wisdom, and that wisdom is not foresight. But information is the first essential step to all of these." (Arthur C Clark)

09 July 2013

Knowledge Management: Mental Model (Definitions)

"A mental model is a cognitive construct that describes a person's understanding of a particular content domain in the world." (John Sown, "Conceptual Structures: Information Processing in Mind and Machine", 1984)

"A mental model is a data structure, in a computational system, that represents a part of the real world or of a fictitious world." (Alan Granham, "Mental Models as Representations of Discourse and Text", 1987)

"[…] a mental model is a mapping from a domain into a mental representation which contains the main characteristics of the domain; a model can be ‘run’ to generate explanations and expectations with respect to potential states. Mental models have been proposed in particular as the kind of knowledge structures that people use to understand a specific domain […]" (Helmut Jungermann, Holger Schütz & Manfred Thuering, "Mental models in risk assessment: Informing people about drugs", Risk Analysis 8 (1), 1988)

 "A mental model is a knowledge structure that incorporates both declarative knowledge (e.g., device models) and procedural knowledge (e.g., procedures for determining distributions of voltages within a circuit), and a control structure that determines how the procedural and declarative knowledge are used in solving problems (e.g., mentally simulating the behavior of a circuit)." (Barbara Y White & John R Frederiksen, "Causal Model Progressions as a Foundation for Intelligent Learning Environments", Artificial Intelligence 42, 1990)

"’Mental models’ are deeply ingrained assumptions, generalizations, or even pictures or images that influence how we understand the world and how we take action. [...] Mental models are deeply held internal images of how the world works, images that limit us to familiar ways of thinking and acting." (Peter Senge, "The Fifth Discipline”, 1990)

"[A mental model] is a relatively enduring and accessible, but limited, internal conceptual representation of an external system (historical, existing, or projected) [italics in original] whose structure is analogous to the perceived structure of that system." (James K Doyle & David N Ford, "Mental models concepts revisited: Some clarifications and a reply to Lane", System Dynamics Review 15 (4), 1999)

"In broad terms, a mental model is to be understood as a dynamic symbolic representation of external objects or events on the part of some natural or artificial cognitive system. Mental models are thought to have certain properties which make them stand out against other forms of symbolic representations." (Gert Rickheit & Lorenz Sichelschmidt, "Mental Models: Some Answers, Some Questions, Some Suggestions", 1999)

"A mental model is conceived […] as a knowledge structure possessing slots that can be filled not only with empirically gained information but also with ‘default assumptions’ resulting from prior experience. These default assumptions can be substituted by updated information so that inferences based on the model can be corrected without abandoning the model as a whole. Information is assimilated to the slots of a mental model in the form of ‘frames’ which are understood here as ‘chunks’ of knowledge with a well-defined meaning anchored in a given body of shared knowledge." (Jürgen Renn, “Before the Riemann Tensor: The Emergence of Einstein’s Double Strategy", 2005)

"A mental model is a mental representation that captures what is common to all the different ways in which the premises can be interpreted. It represents in 'small scale' how 'reality' could be - according to what is stated in the premises of a reasoning problem. Mental models, though, must not be confused with images." (Carsten Held et al, "Mental Models and the Mind", 2006)

"’Mental models’ are deeply ingrained assumptions, generalizations, or even pictures or images that influence how we understand the world and how we take action." (Jossey-Bass Publishers, "The Jossey-Bass Reader on Educational Leadership”, 2nd Ed. 2007)

"A mental model is an internal representation with analogical relations to its referential object, so that local and temporal aspects of the object are preserved." (Gert Rickheit et al, "The concept of communicative competence" [in "Handbook of Communication Competence"], 2008)

"Internal representations constructed on the spot when required by demands of an external task or by a self-generated stimulus. It enables activation of relevant schemata, and allows new knowledge to be integrated. It specifies causal actions among concepts that take place within it, and it can be interacted with in the mind." (Daniel Churchill, "Mental Models" [in "Encyclopedia of Information Technology Curriculum Integration"] , 2008)

"Mental models are representations of reality built in people’s minds. These models are based on arrangements of assumptions, judgments, and values. A main weakness of mental models is that people’s assumptions and judgments change over time and are applied in inconsistent ways when building explanations of the world." (Luis F Luna-Reyes, "System Dynamics to Understand Public Information Technology", 2008)

"A mental model is the collection of concepts and relationships about the image of real world things we carry in our heads" (Hassan Qudrat-Ullah, "System Dynamics Based Technology for Decision Support", 2009)

"A mental recreation of the states of the world reproduced cognitively in order to offer itself as a basis for reasoning." (Eshaa M Alkhalifa, "Open Student Models", 2009)

[Shared Mental Model:] "A mental model that is shared among team members, and may include: 1) task-specific knowledge, 2) task-related knowledge, 3) knowledge of teammates and 4) attitudes/beliefs." (Rosemarie Reynolds et al, "Measuring Shared Mental Models in Unmanned Aircraft Systems", 2015) 

"A network of knowledge content, as well as the relationships among the content."(Rosemarie Reynolds et al, "Measuring Shared Mental Models in Unmanned Aircraft Systems", 2015)

"A mental model (aka mental representation/image/picture) is a mental structure that attempts to model (depict, imagine) how real or imaginary things look like, work or fit together." (The Web of Knowledge) [source]

Quotes on "Mental Models" at the-web-of-knowledge.blogspot.com.

07 July 2013

Knowledge Management: Concept Map (Definitions)

"Concept maps are built of nodes connected by connectors, which have written descriptions called linking phrases instead of polarity of strength. Concept maps can be used to describe conceptual structures and relations in them and the concept maps suit also aggregation and preservation of knowledge" (Hannu Kivijärvi et al, "A Support System for the Strategic Scenario Process", 2008) 

"A hierarchal picture of a mental map of knowledge." (Gregory MacKinnon, "Concept Mapping as a Mediator of Constructivist Learning", 2009)

"A tool that assists learners in the understanding of the relationships of the main idea and its attributes, also used in brainstorming and planning." (Diane L Judd, "Constructing Technology Integrated Activities that Engage Elementary Students in Learning", 2009)

"Concept maps are graphical knowledge representations that are composed to two components: (1) Nodes: represent the concepts, and (2) Links: connect concepts using a relationship." (Faisal Ahmad et al, "New Roles of Digital Libraries", 2009)

"A concept map is a diagram that depicts concepts and their hierarchical relationships." (Wan Ng & Ria Hanewald, "Concept Maps as a Tool for Promoting Online Collaborative Learning in Virtual Teams with Pre-Service Teachers", 2010)

"A diagram that facilitates organization, presentation, processing and acquisition of knowledge by showing relationships among concepts as node-link networks. Ideas in a concept map are represented as nodes and connected to other ideas/nodes through link labels." (Olusola O Adesope & John C Nesbit, "A Systematic Review of Research on Collaborative Learning with Concept Maps", 2010)

"A visual construct composed of encircled concepts (nodes) that are meaningfully inter-connected by descriptive concept links either directly, by branch-points (hierarchies), or indirectly by cross-links (comparisons). The construction of a concept map can serve as a tool for enhancing communication, either between an author and a student for a reading task, or between two or more students engaged in problem solving. (Dawndra Meers-Scott, "Teaching Critical Thinking and Team Based Concept Mapping", 2010)

"Are graphical ways of working with ideas and presenting information. They reveal patterns and relationships and help students to clarify their thinking, and to process, organize and prioritize. The visual representation of information through word webs or diagrams enables learners to see how the ideas are connected and understand how to group or organize information effectively." (Robert Z Zheng & Laura B Dahl, "Using Concept Maps to Enhance Students' Prior Knowledge in Complex Learning", 2010)

"Concept maps are hierarchical trees, in which concepts are connected with labelled, graphical links, most general at the top." (Alexandra Okada, "Eliciting Thinking Skills with Inquiry Maps in CLE", 2010)

"One powerful knowledge presentation format, devised by Novak, to visualize conceptual knowledge as graphs in which the nodes represent the concepts, and the links between the nodes are the relationships between these concepts." (Diana Pérez-Marín et al, "Adaptive Computer Assisted Assessment", 2010)

"A form of visualization showing relationships among concepts as arrows between labeled boxes, usually in a downward branching hierarchy." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A graphical depiction of relationships ideas, principals, and activities leading to one major theme." (Carol A Brown, "Using Logic Models for Program Planning in K20 Education", 2013)

"A diagram that presents the relationships between concepts." (Gwo-Jen Hwang, "Mobile Technology-Enhanced Learning", 2015)

"A graphical two-dimensional display of knowledge. Concepts, usually presented within boxes or circles, are connected by directed arcs that encode, as linking phrases, the relationships between the pairs of concepts." (Anna Ursyn, "Visualization as Communication with Graphic Representation", 2015)

"A graphical tool for representing knowledge structure in a form of a graph whose nodes represent concepts, while arcs between nodes correspond to interrelations between them." (Yigal Rosen & Maryam Mosharraf, "Evidence-Centered Concept Map in Computer-Based Assessment of Critical Thinking", 2016) 

"Is a directed graph that shows the relationship between the concepts. It is used to organize and structure knowledge." (Anal Acharya & Devadatta Sinha, "A Web-Based Collaborative Learning System Using Concept Maps: Architecture and Evaluation", 2016)

"A graphic depiction of brainstorming, which starts with a central concept and then includes all related ideas." (Carolyn W Hitchens et al, "Studying Abroad to Inform Teaching in a Diverse Society", 2017)

"A graphic visualization of the connections between ideas in which concepts (drawn as nodes or boxes) are linked by explanatory phrases (on arrows) to form a network of propositions that depict the quality of the mapper’s understanding" (Ian M Kinchin, "Pedagogic Frailty and the Ecology of Teaching at University: A Case of Conceptual Exaptation", 2019)

"A diagram in which related concepts are linked to each other." (Steven Courchesne &Stacy M Cohen, "Using Technology to Promote Student Ownership of Retrieval Practice", 2020)

Knowledge Management: Conceptual Model (Definitions)

"A conceptual model is a qualitative description of the system and includes the processes taking place in the system, the parameters chosen to describe the processes, and the spatial and temporal scales of the processes." (A Avogadro & R C Ragaini, "Technologies for Environmental Cleanup", 1993)

"A conceptual model is a model of the projected system that is independent of implementation details." (Michael Worboys, "GIS: A Computing Perspective", 1995)

"A conceptual model is what in the model theory is called a set of formulas making statements about the world." (Dickson Lukose [Eds.], "Conceptual Structures: Fulfilling Peirce's Dream" Vol 5, 1997)

"A conceptual model is a representation of the system expertise using this formalism. An internal model is derived from the conceptual model and from a specification of the system transactions and the performance constraints." (Zbigniew W. Ras & Andrzej Skowron [Eds.], Foundations of Intelligent Systems: 10th International Symposium Vol 10, 1997)

"A conceptual model is one which reflects reality by placing words which are concepts into the model in the same way that the model aeroplane builder puts wings, a fuselage, and a cockpit together." (Lynn Basford & ‎Oliver Slevin, "Theory and Practice of Nursing: An Integrated Approach to Caring Practice", 2003) 

"A conceptual model is simply a framework or schematic to understand the interaction of workforce education and development systems with other variables in a society." (Jay W Rojewski, "International Perspectives on Workforce Education and Development", 2004) 

"A conceptual model is a mental image of a system, its components, its interactions. It lays the foundation for more elaborate models, such as physical or numerical models. A conceptual model provides a framework in which to think about the workings of a system or about problem solving in general. An ensuing operational model can be no better than its underlying conceptualization." (Henry N Pollack, "Uncertain Science … Uncertain World", 2005)

"A particular kind of learning object design to be supplied to learners to support their mental modeling." (Daniel Churchill, "Mental Models" [in "Encyclopedia of Information Technology Curriculum Integration"], 2008)

"The concepts and constructs about real work things we have in our heads are called mental model." (Hassan Qudrat-Ullah, "System Dynamics Based Learning Environments" [in "Encyclopedia of Information Technology Curriculum Integration"], 2008)

"Representations of real or imaginary structure in the human mind enabling orientation as well as goal orientated actions and movements" (Ralf Wagner, "Customizing Multimedia with Multi-Trees" [in "Encyclopedia of Multimedia Technology and Networking" 2nd Ed.], 2009)

"A conceptual model is a qualitative description of 'some aspect of the behaviour of a natural system'. This description is usually verbal, but may also be accompanied by figures and graphs." (Howard S. Wheater et al., "Groundwater Modelling in Arid and Semi-Arid Areas, 2010) 

"[…] a conceptual model is a diagram connecting variables and constructs based on theory and logic that displays the hypotheses to be tested." (Mary Wolfinbarger Celsi et al, "Essentials of Business Research Methods", 2011) 

"A conceptual model of an interactive application is, in summary: the structure of the application - the objects and their operations, attributes, and relation-ships; an idealized view of the how the application works – the model designers hope users will internalize; the mechanism by which users accomplish the tasks the application is intended to support." (Jeff Johnson & Austin Henderson, "Conceptual Models", 2011)

"Simply put, a conceptual model is a simplified representation of reality, devised for a certain purpose and seen from a certain point of view."(David W Emble & Bernhard Thalheim, "Handbook of Conceptual Modeling", 2012) 

"Briefly, a conceptual model is the configuration of conceptual elements and the navigation between them. As such, a conceptual model is the foundation of the user interface of any interactive system." (Avi Parush, "Conceptual Design for Interactive Systems", 2015)

"A conceptual model is a framework that is initially used in research to outline the possible courses of action or to present an idea or thought. When a conceptual model is developed in a logical manner, it will provide a rigor to the research process." (N Elangovan & R Rajendran, "Conceptual Model: A Framework for Institutionalizing the Vigor in Business Research", 2015) 

"A model or conceptual model is a schematic or representation that describes how something works. We create and adapt models all the time without realizing it. Over time, as you gain more information about a problem domain, your model will improve to better match reality." (James Padolsey, "Clean Code in JavaScript", 2020)

Quotes on "Conceptual Models" at the-web-of-knowledge.blogspot.com.

28 June 2013

Knowledge Management: Cognitive Map (Definitions)

"A cognitive map is a specific way of representing a person's assertions about some limited domain, such as a policy problem. It is designed to capture the structure of the person's causal assertions and to generate the consequences that follow front this structure." (Robert M Axelrod, "Structure of Decision: The cognitive maps of political elites", 1976)

"A cognitive map is the representation of thinking about a problem that follows from the process of mapping." (Colin Eden, "Analyzing cognitive maps to help structure issues or problems", 2002)

"A mental representation of a portion of the physical environment and the relative locations of points within it." (Andrew M Colman, "A Dictionary of Psychology" 3rd Ed, 2008)

"A mental model (or map) of the external environment which may be constructed following exploratory behaviour." (Michael Allaby, "A Dictionary of Zoology" 3rd Ed., 2009)

"An FCM [Fuzzy Cognitive Map] is a directed graph with concepts like policies, events etc. as nodes and causalities as edges. It represents causal relationship between concepts." (Florentin Smarandache &  W B Vasantha Kandasamy, "Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps", 2014)

"A conceptual tool that provides a representation of particular natural or social environments in the form of a model." (Evangelos C Papakitsos et al, "The Challenges of Work-Based Learning via Systemic Modelling in the European Union", 2020)

"A representation of the conceptualization that the subject constructs of the system in which he evolves. The set of cognitive representations that emerge make it possible to understand his actions, the links between the factors structuring the cognitive patterns dictating his behaviors." (Henda E Karray & Souhaila Kammoun, "Strategic Orientation of the Managers of a Tunisian Family Group Before and After the Revolution", 2020)

"A cognitive map is a type of mental representation which serves an individual to acquire, code, store, recall, and decode information about the relative locations and attributes of phenomena in their everyday or metaphorical spatial environment." (Wikipedia) [source]

13 June 2013

Knowledge Management: Tacit Knowledge (Definitions)

"Know-how that is difficult to articulate and share; intuition or skills that cannot easily be put into words." (Martin J Eppler, "Managing Information Quality" 2nd Ed., 2006)

"The domain of subjective, cognitive, and experimental knowledge that is highly personal and difficult to formalize." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"The knowledge that a person retains in their mind. It is relatively hard to transfer to others and to disseminate widely. Also known as implicit knowledge." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"Knowledge that is based on experience and not easy to share, document, or explain." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"Knowledge that resides in people's heads. Also referred to as know-how, rules of thumb, or heuristics." (Joan C Dessinger, "Fundamentals of Performance Improvement" 3rd Ed., 2012)

"Tacit knowledge is sometimes referred to as knowledge inside people’s heads. It includes the skills and intuition that experienced people apply as a matter of course in their work. Tacit knowledge is contrasted with explicit knowledge, which is knowledge that is documented in a sharable form. One of the goals of knowledge management is to enable tacit knowledge to be shared by making it explicit knowledge." (Laura Sebastian-Coleman, "Measuring Data Quality for Ongoing Improvement ", 2012)

"Undocumented information." (Project Management Institute, "Software Extension to the PMBOK® Guide 5th Ed", 2013)

"Personal knowledge that can be difficult to articulate and share such as beliefs, experience, and insights." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK Guide)", 2017)

07 June 2013

Knowledge Management: Taxonomy (Definitions)

"A classification system." (Ruth C Clark & Chopeta Lyons, "Graphics for Learning", 2004)

"A hierarchical structure within which related items are organized, classified, or categorized, thus illustrating the relationships between them." (Richard Caladine, "Taxonomies for Technology", 2008)

"A taxonomy is a hierarchical structure displaying parent-child relationships (a classification). A taxonomy extends a vocabulary and is a special case of a the more general ontology." (Troels Andreasen & Henrik Bulskov, "Query Expansion by Taxonomy", 2008)

"An orderly classification that explicitly expresses the relationships, usually hierarchical (e.g., genus/species, whole/part, class/instance), between and among the things being classified." (J P Getty Trust, "Introduction to Metadata" 2nd Ed., 2008)

"This term traditionally refers to the study of the general principles of classification. It is widely used to describe computer-based systems that use hierarchies of topics to help users sift through information." (Craig F Smith & H Peter Alesso, "Thinking on the Web: Berners-Lee, Gödel and Turing", 2008)

"A kind of classification method which organizes all kinds of things into predefined hierarchical structure." (Yong Yu et al, "Social Tagging: Properties and Applications", 2010)

"Any system of categories used to organize something, including documents, often less comprehensive than a thesaurus." (Steven Woods et al, "Knowledge Dissemination in Portals", 2011)

"Generally, a collection of controlled vocabulary terms organized into a structure of parent-child relationships. Each term is in at least one relationship with another term in the taxonomy. Each parent's relationship with all of its children are of only one type (whole-part, genus-species, or type-instance). The addition of associative relationships creates a thesaurus." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A definitional hierarchy of concepts. Traditional taxonomies are tree-structured (a concept is assumed to have exactly one superconcept and multiple subconcepts). The higher a concept is positioned in the definitional hierarchy, the more individuals it describes (the comprehension of the concept), but the less definitional properties are needed (the meaning of a concept)." (Marcus Spies & Said Tabet, "Emerging Standards and Protocols for Governance, Risk, and Compliance Management", 2012) 

"A hierarchical representation of metadata. The top level is the category, and each subsequent level provides a refinement (detail) of the top-level term." (Charles Cooper & Ann Rockley, "Managing Enterprise Content: A Unified Content Strategy" 2nd Ed., 2012)

"A hierarchical structure of information components, for example, a subject, business–unit, or functional taxonomy, any part of which can be used to classify a content item in relation to other items in the structure." (Robert F Smallwood, "Managing Electronic Records: Methods, Best Practices, and Technologies", 2013)

"A classification of text" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"A hierarchical structure of information components (e.g., a subject, business unit, or functional taxonomy), any part of which can be used to classify a content item in relation to other items in the structure." (Robert F Smallwood, "Information Governance: Concepts, Strategies, and Best Practices", 2014)

"provides context within the ontology. Taxonomies are used to capture hierarchical relationships between elements of interest. " (Judith S Hurwitz, "Cognitive Computing and Big Data Analytics", 2015)

"Taxonomy is the science and practice of classification. Taxonomies are used when categorizing real-life as well as artificial phenomenon and the aim is to make systematic studies easier." (Ulf Larson et al, "Guidance for Selecting Data Collection Mechanisms for Intrusion Detection", 2015)

"A taxonomy is a hierarchy that is created by a set of interconnected class inclusion relationship." (Robert J Glushko, "The Discipline of Organizing: Professional Edition" 4th Ed., 2016)

"A hierarchical structure of information components, for example, a subject, business unit, or functional taxonomy, any part of which can be used to classify a content item in relation to other items in the structure." (Robert F Smallwood, "Information Governance for Healthcare Professionals", 2018)

06 June 2013

Knowledge Management: Ontology (Definitions)

"A data model that represents the entities that are defined and evaluated by its own attributes, and organized according to a hierarchy and a semantic. Ontologies are used for representing knowledge on the whole of a specific domain or on of it." (Gervásio Iwens et al, "Programming Body Sensor Networks", 2008)

"An ontology specifies a conceptualization, that is, a structure of related concepts for a given domain." (Troels Andreasen & Henrik Bulskov, "Query Expansion by Taxonomy", 2008)

"A semantic structure useful to standardize and provide rigorous definitions of the terminology used in a domain and to describe the knowledge of the domain. It is composed of a controlled vocabulary, which describes the concepts of the considered domain, and a semantic network, which describes the relations among such concepts. Each concept is connected to other concepts of the domain through semantic relations that specify the knowledge of the domain. A general concept can be described by several terms that can be synonyms or characteristic of different domains in which the concept exists. For this reason the ontologies tend to have a hierarchical structure, with generic concepts/terms at the higher levels of the hierarchy and specific concepts/terms at the lover levels, connected by different types of relations." (Mario Ceresa, "Clinical and Biomolecular Ontologies for E-Health", Handbook of Research on Distributed Medical Informatics and E-Health, 2009)

"In the context of knowledge sharing, the chapter uses the term ontology to mean a specification of conceptual relations. An ontology is the concepts and relationships that can exist for an agent or a community of agents. The chapter refers to designing ontologies for the purpose of enabling knowledge sharing and re-use." (Ivan Launders, "Socio-Technical Systems and Knowledge Representation", 2009)

 "The systematic description of a given phenomenon, which often includes a controlled vocabulary and relationships, captures nuances in meaning and enables knowledge sharing and reuse. Typically, ontology defines data entities, data attributes, relations and possible functions and operations." (Mark Olive, "SHARE: A European Healthgrid Roadmap", 2009)

"Those things that exist are those things that have a formal representation within the context of a machine. Knowledge commits to an ontology if it adheres to the structure, vocabulary and semantics intrinsic to a particular ontology i.e. it conforms to the ontology definition. A formal ontology in computer science is a logical theory that represents a conceptualization of real world concepts." (Philip D. Smart, "Semantic Web Rule Languages for Geospatial Ontologies", 2009)

"A formal representation of a set of concepts within a domain and the relationships between those concepts. It is used to reason about the properties of that domain, and may be used to define the domain." (Yong Yu et al, "Social Tagging: Properties and Applications", 2010)

"Is set of well-defined concepts describing a specific domain." (Hak-Lae Kim et al, "Representing and Sharing Tagging Data Using the Social Semantic Cloud of Tags", 2010)

"An ontology is a 'formal, explicit specification of a shared conceptualisation'. It is composed of concepts and relations structured into hierarchies (i.e. they are linked together by using the Specialisation/Generalisation relationship). A heavyweight ontology is a lightweight ontology (i.e. an ontology simply based on a hierarchy of concepts and a hierarchy of relations) enriched with axioms used to fix the semantic interpretation of concepts and relations." (Francky Trichet et al, "OSIRIS: Ontology-Based System for Semantic Information Retrieval and Indexation Dedicated to Community and Open Web Spaces", 2011)

"The set of the things that can be dealt with in a particular domain, together with their relationships." (Steven Woods et al, "Knowledge Dissemination in Portals", 2011) 

"In semantic web and related technologies, an ontology (aka domain ontology) is a set of taxonomies together with typed relationships connecting concepts from the taxonomies and, possibly, sets of integrity rules and constraints defining classes and relationships." (Marcus Spies & Said Tabet, "Emerging Standards and Protocols for Governance, Risk, and Compliance Management", 2012)

"High-level knowledge and data representation structure. Ontologies provide a formal frame to represent the knowledge related with a complex domain, as a qualitative model of the system. Ontologies can be used to represent the structure of a domain by means of defining concepts and properties that relate them." (Lenka Lhotska et al, "Interoperability of Medical Devices and Information Systems", 2013)

"(a) In computer science and information science, an ontology formally represents knowledge as a set of concepts within a domain, and the relationships between pairs of concepts. It can be used to model a domain and support reasoning about concepts. (b) In philosophy, ontology is the study of the nature of being, becoming, existence , or reality , as well as the basic categories of being and their relations. Traditionally listed as a part of the major branch of philosophy known as metaphysics, ontology deals with questions concerning what entities exist or can be said to exist, and how such entities can be grouped, related within a hierarchy, and subdivided according to similarities and differences." (Ronald J Lofaro, "Knowledge Engineering Methodology with Examples", 2015)

"It is a shared structure which classify and organizes all the entities of a given domain." (T R Gopalakrishnan Nair, "Intelligent Knowledge Systems", 2015)

"The study of how things relate. Used in big data to analyze seemingly unrelated data to discover insights." (Jason Williamson, "Getting a Big Data Job For Dummies", 2015)

"An ontology is a formal, explicit specification of a shared conceptualization." (Fu Zhang et al, "A Review of Answering Queries over Ontologies Based on Databases", 2016)

03 June 2013

Knowledge Management: Explicit Knowledge (Definitions)

"Knowledge that is easily codified, shared, documented, and explained." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"The knowledge that deals with objective, rational, and technical knowledge (data, policies, procedures, software, documents, etc.)." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"Explicit knowledge is information that is captured in a way that it can be shared. People can learn it without having to rely directly on other people. In knowledge management practice, explicit knowledge is contrasted with tacit knowledge, which is knowledge that is inside people’s heads." (Laura Sebastian-Coleman, "Measuring Data Quality for Ongoing Improvement", 2012)

"Recorded information, for example, a written policy or procedure." (Joan C Dessinger, "Fundamentals of Performance Improvement" 3rd Ed., 2012)

"Knowledge that can be codified using symbols such as words, numbers, and pictures." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK Guide)", 2017)

02 June 2013

Knowledge Management: Knowledge Management (Definitions)

"The conscious and systematic facilitation of knowledge creation or development, diffusion or transfer, safeguarding, and use at the individual, team- and organizational level." (Martin J Eppler, "Managing Information Quality" 2nd Ed., 2006)

"The field of study that relates to the centralized management of a company’s corporate knowledge and information assets in order to provide this knowledge to as many company staff members as possible and thus encourage better and more consistent decision making." (Evan Levy & Jill Dyché, "Customer Data Integration", 2006)

"Discipline that intends to provide, at its most suitable level, the accurate information and knowledge for the right people, whenever they may be needed and at their best convenience." (J Ares, "Guidelines for Deploying a Knowledge Management System", 2008)

"The process of creating, capturing and organizing knowledge objects. A knowledge object might be a research report, a budget for the development of a new product, or a video presentation. Knowledge Management programs seek to capture objects in a repository that is searchable and accessible in electronic form." (Craig F Smith & H Peter Alesso, "Thinking on the Web: Berners-Lee, Gödel and Turing", 2008)

"The process established to capture and use specific knowledge in an organization for the purpose of improving organizational performance." (Murray E Jennex, "Technologies in Support of Knowledge Management Systems", 2009)

"1.The management of an environment where people generate tacit knowledge, render it into explicit knowledge, and feed it back to the organization. The cycle forms a base for more tacit knowledge, which keeps the cycle going in an intelligent learning organization. (Brackett 2011) 2.The discipline that fosters organizational learning and the management of intellectual capital as an enterprise resource." (DAMA International, "The DAMA Dictionary of Data Management" 1st Ed., 2010)

"The process that helps organizations identify, select, organize, disseminate, and transfer important information and expertise that are part of the organization's memory and that may reside in unstructured form within the organization." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"Knowledge management is a set of practices related to how organizations learn from their own experiences. Many of these practices focus on ensuring that what employees know and learn is captured in a shareable form (explicit knowledge)." (Laura Sebastian-Coleman, "Measuring Data Quality for Ongoing Improvement ", 2012)

"The accumulation, organization, and use of experience and lessons learned, which can be leveraged to improve future decision-making efforts. KM often involves listing and indexing subject matter experts, project categories, reports, studies, proposals, and other intellectual property sources or outputs that are retained to build corporate memory. Good KM systems help train new employees and reduce the impact of turnover and retirement of key employees." (Robert F Smallwood, "Information Governance: Concepts, Strategies, and Best Practices", 2014)

"The process of capturing, using, leveraging, and sharing organizational knowledge." (Sally-Anne Pitt, "Internal Audit Quality", 2014)

"The intentional process of creation, acquisition and sharing of knowledge and its utilization as a key factor in the creation of added value. It is an inextricably human and cooperative process." (António C Moreira & Ricardo A Zimmermann, "Electronic Government: Challenges for Public Services Consumer Behaviour and Value Creation", 2015)

"Knowledge management is considered as a systematic process of managing knowledge assets, processes, and environment to facilitate the creation, organization, sharing, utilization, and measurement of knowledge to achieve the strategic aims of an organization." (Haitham Alali et al, "Knowledge Sharing Success Model of Virtual Communities of Practice in Healthcare Sector", 2016)

"Knowledge management promotes activities and processes to acquire, create, document, and share formal explicit knowledge and informal implicit knowledge. Knowledge management involves identifying a group of people who have a need to share knowledge, developing technological support that enables knowledge sharing, and creating a process for transferring and disseminating knowledge." (Ciara Heavin & Daniel J Power, "Decision Support, Analytics, and Business Intelligence" 3rd Ed., 2017)

"The process of creating, sharing, using and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieving organizational objectives by making the best use of knowledge." (Izabella V Lokshina et al, "Internet of Things and Big Data-Driven Data Analysis Services for Third Parties", 2019)

"The methods and underlying policies for sharing information effectively so that the sum of the skills, experience and entrepreneurial attributes of all stakeholders is greater than the sum of the individual parts. If done well, each stakeholder also benefits, thus increasing the ‘sum of the individual parts’ that go on to increase the ‘sum of the whole’ in a virtuous circle." (Sue Milton, "Data Privacy vs. Data Security", 2021)

01 June 2013

Knowledge Management: Knowledge (Definitions)

"Justified true belief, the know-what/-how/-who/-why that individuals use to solve problems, make predictions or decisions, or take actions." (Martin J Eppler, "Managing Information Quality" 2nd Ed., 2006)

"An individual’s understanding of facts or information. Knowledge provides the basis for performing a skill that an individual must have to perform a task successfully." (Sally A Miller et al, "People CMM: A Framework for Human Capital Management" 2nd Ed., 2009)

"1.Generally, expertise; familiarity gained through experience or association; cognizance, the fact or condition of knowing something; the acquaintance with or the understanding of something; the fact or condition of being aware of something, of apprehending truth or fact." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"The body of information and facts about a specific subject. Knowledge implies familiarity, awareness, and understanding of information as it applies to an environment. A key characteristic of knowledge is that 'new' knowledge can be derived from 'old' knowledge." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"The fact or condition of knowing something with familiarity gained through experience or association. Knowledge adds understanding and retention to information." (Craig S Mullins, "Database Administration", 2012)

"The metadata about all the changes that a participant has seen and maintains." (Microsoft, "SQL Server 2012 Glossary", 2012)

"A collection of specialized facts, procedures, and judgment rules. Knowledge refers to what one knows and understands. Knowledge is categorized as unstructured, structured, explicit, or implicit. What we know we know we call explicit knowledge. Knowledge that is unstructured and understood, but not clearly expressed, we call implicit knowledge." (Ciara Heavin & Daniel J Power, "Decision Support, Analytics, and Business Intelligence 3rd Ed.", 2017)

"A mixture of experience, values and beliefs, contextual information, intuition, and insight that people use to make sense of new experiences and information." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK® Guide)", 2017)

"Knowing something with the familiarity gained through experience, education, observation, or investigation; it is understanding a process, practice, or technique, or how to use a tool." (Project Management Institute, "Project Manager Competency Development Framework" 3rd Ed., 2017)

"That array of facts and relationships that an individual has available to him or her for the performance of work, it may be part or all of an accepted body of knowledge, or knowledge that has been produced as largely self-generated content by the individual." (Catherine Burke et al, "Systems Leadership" 2nd Ed., 2018)

"The sum of a person’s - or mankind’s - information about and ability to understand the world." (Open Data Handbook)

04 April 2013

Process Management: Roles (Definitions)

"A job type defined in terms of a set of responsibilities." (Atul Apte, "Java Connector Architecture: Building Custom Connectors and Adapters", 2002)

"A set of expectations for behavior; describes the extent to which each individual performs activities related to project." (Timothy J  Kloppenborg et al, "Project Leadership", 2003)

"Specified responsibilities that identify a set of related activities to be performed by a designated individual (e.g., a project manager)." (Richard D Stutzke, "Estimating Software-Intensive Systems: Projects, Products, and Processes", 2005)

"A definition of the behavior and responsibilities of an individual or set of individuals working together as a team." (Bruce MacIsaac & Per Kroll, "Agility and Discipline Made Easy: Practices from OpenUP and RUP", 2006)

"A defined set of work tasks, dependencies, and responsibilities that can be assigned to an individual as a work package. A role describes a collection of tasks that constitute one component of a process, and would normally be performed by an individual." (Sally A Miller et al, "People CMM: A Framework for Human Capital Management" 2nd Ed., 2009)

"The set of expectations in a social system that define the services individuals or groups are supposed to provide." (Alexander Grashow et al, "The Practice of Adaptive Leadership", 2009)

"The characteristic and expected behaviors of an individual, derived from his or her responsibilities and preferences in providing value to the organization." (David Lyle & John G Schmidt, "Lean Integration", 2010)

"1.Generally, a label assigned to a set of connected behaviors, rights and obligations. 2.In data modeling, the way in which entities of one type relate to entities of another type in a relationship. 3.In data security, a name used to refer to the logical set of related responsibilities assignable to a person or organization, and to parties with these assigned responsibilities." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A defined function to be performed by a project team member, such as testing, filing, inspecting, coding." (Cynthia Stackpole, "PMP® Certification All-in-One For Dummies®", 2011)

"Description of specific skills, qualifications and work profiles in software development. These should be filled by the persons (responsible for these roles) in the project." (Tilo Linz et al, "Software Testing Foundations" 4th Ed., 2014)

"Usual or expected functionality of an actor in the context of an activity or a business process; an actor can have one or several roles. " (Gilbert Raymond & Philippe Desfray, "Modeling Enterprise Architecture with TOGAF", 2014)

"A defined function to be performed by a project team member, such as testing, filing, inspecting, or coding." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK Guide )", 2017)

"In ITIL, this is a set of responsibilities, activities and authorities granted to a person or team. A role is defined in a process. One person or team may have multiple roles, for example the roles of configuration manager and change manager may be carried out by a single person." (Brian Johnson & Leon-Paul de Rouw, "Collaborative Business Design", 2017)

"A defined function to be performed by a project team member, such as testing, filing, inspecting, coding." (Jeffrey K Pinto, "Project Management: Achieving Competitive Advantage" 5th Ed., 2018)

"A set of responsibilities, activities and authorities granted to a person/team." (ITIL)

03 April 2013

Process Management: Baseline (Definitions)

"A documented characterization of the actual results achieved by following a process, which is used as a benchmark for comparing actual process performance against expected process performance." (Sandy Shrum et al, "CMMI: Guidelines for Process Integration and Product Improvement", 2003)

"A range of expected results that would normally be achieved by following a defined process. Often expressed in terms of the process control limits defined by the discipline of statistical process control." (Richard D Stutzke, "Estimating Software-Intensive Systems: Projects, Products, and Processes", 2005)

"Documented process performance values used as a reference to compare actual and expected process performance." (Richard D Stutzke, "Estimating Software-Intensive Systems: Projects, Products, and Processes", 2005)

"A documented characterization of the range of expected results that would normally be achieved by following a specific process under typical circumstances." (Sally A Miller et al, "People CMM: A Framework for Human Capital Management" 2nd Ed., 2009)

"A documented characterization of the results achieved by following a process that is used as a benchmark for comparing actual process performance against expected process performance." (Sally A Miller et al, "People CMM: A Framework for Human Capital Management" 2nd Ed., 2009)

[capability baseline:] "A statistically based description of the performance or results of a process that has been performed repeatedly. Capability baselines can quantify attributes of the process (e.g., effort or duration) or of the product produced by the process (e.g., amount or quality). Control charts used in statistical process control are one form of capability baseline. However, other statistical representations may be more appropriate, depending on the nature of the data being characterized. The purpose of a capability baseline is to predict outcomes and to interpret the results of process performance." (Sally A Miller et al, "People CMM: A Framework for Human Capital Management" 2nd Ed., 2009)

Business Intelligence: Lagging Indicator (Definitions)

"When something consistently occurs a given period of time after something else, it is sometimes called a lagging indicator. The term is frequently applied to a curve of something that is correlated with the curve of something else, except it occurs a fixed period of time later (i.e., is shifted to the right on a graph with a time scale). For example, retail prices many times are lagging indicators of wholesale prices. Conversely, wholesale prices are often leading indicators of retail prices." (Robert L Harris, Information Graphics: A Comprehensive Illustrated Reference, 1996)

"An indicator that follows the occurrence of something; hence used to determine the performance of an occurrence or an event. By tracking lagging indicators, one reacts to the results. For example, the high and low temperature, precipitation, and humidity of a given day." (Lynne Hambleton, "Treasure Chest of Six Sigma Growth Methods, Tools, and Best Practices", 2007)

"Data that reflects a slower reaction to economic or market changes; useful to describe trends." (Annetta Cortez & Bob Yehling, "The Complete Idiot's Guide® To Risk Management", 2010)

"An indicator that precedes the occurrence of something; hence, such indicators are used to signal the upcoming occurrence of an event. By tracking leading indicators, one can prepare or anticipate the subsequent event and be proactive. For example, barometric pressure and doplar radar of a surrounding region are indicators of ensuing weather." (Clyde M Creveling, "Six Sigma for Technical Processes: An Overview for R Executives, Technical Leaders, and Engineering Managers", 2006)

"Information that helps to forecast an increase in risk likelihood or severity before it appears in actual risk measures." (Annetta Cortez & Bob Yehling, "The Complete Idiot's Guide® To Risk Management", 2010)

"Backward-looking performance indicators that represent the results of previous actions. Characterizing historical performance, lagging indicators frequently focus on results at the end of a time period; e.g., third-quarter sales. A balanced scorecard should contain a mix of lagging and leading indicators." (Intrafocus) 

29 March 2013

Process Management: (Capability) Maturity Model (Definitions)

[capability maturity model:] "A model that contains the essential elements of effective processes for one or more disciplines and describes an evolutionary improvement path from ad hoc, immature processes to disciplined, mature processes with improved quality and effectiveness." (Sandy Shrum et al, "CMMI®: Guidelines for Process Integration and Product Improvement", 2003)

[capability maturity model (CMM):] "A formal document describing the requirements for a 'good' process, using some structure or taxonomy. Process maturity models define how you “ought to” produce a product, and typically require that the process be defined, documented, taught, practiced, measured, improved, and enforced." (Richard D Stutzke, "Estimating Software-Intensive Systems: Projects, Products, and Processes", 2005)

"A model to categorize the maturity of an organization by different levels. Most famous are the Capability Maturity Model (CMM) and its successor, the Capability Maturity Model Integration (CMMI). Following this approach, many organizations have developed SOA maturity models." (Nicolai M Josuttis, "SOA in Practice", 2007)

"A Capability Maturity Model (CMM) is an evolutionary roadmap for implementing the vital practices from one or more domains of organizational process. It contains the essential elements of effective processes for one or more disciplines. It describes an evolutionary improvement path from an ad hoc, immature process to a disciplined, mature process with improved quality and effectiveness." (Sally A Miller et al, "People CMM: A Framework for Human Capital Management 2nd Ed.", 2009)

"A structured collection of characteristics of effective processes at progressive levels of quality and effectiveness. A maturity model provides a common language and a shared vision for process improvement, a standard for benchmarking, and a framework for prioritizing actions. A maturity model assumes a natural evolutionary path for organizational process improvement." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A framework that describes, for a specific area of interest, a number of levels of sophistication at which activities in this area can be carried out." (Jim Davis & Aiman Zeid, "Business Transformation: A Roadmap for Maximizing Organizational Insights", 2014)

"First introduced by the Carnegie Mellon Software Engineering Institute in 1991 to improve the process of software development. However, their broader applicability was recognized, and the model was expanded in 2000 to apply to enterprise-wide process improvement." (Sally-Anne Pitt, "Internal Audit Quality", 2014)

[Capability Maturity Model Integration (CMMI):] "A process improvement approach that provides organizations with the essential elements of effective processes, which will improve their performance." (Adam Gordon, "Official (ISC)2 Guide to the CISSP CBK" 4th Ed.", 2015)

[capability maturity model integration (CMMI):] "A process model that captures the organization’s maturity and fosters continuous improvement." (Shon Harris & Fernando Maymi, "CISSP All-in-One Exam Guide" 8th Ed., 2018)

"A set of structured levels that describe how well an organization can reliably and sustainably produce required outcomes." (Yassine Maleh et al, 'Strategic IT Governance and Performance Frameworks in Large Organizations", 2019)

[Capability Maturity Model (CMM):] "A five level staged framework that describes the key elements of an effective software process. The Capability Maturity Model covers best practices for planning, engineering and managing software development and maintenance ." (IQBBA)

[Capability Maturity Model Integration (CMMI):] "A framework that describes the key elements of an effective product development and maintenance process. The Capability Maturity Model Integration covers best-practices for planning, engineering and managing product development and maintenance. (CMMI)

"A structured collection of elements that describe certain aspects of maturity in an organization, and aid in the definition and understanding of an organization's processes. A maturity model often provides a common language, shared vision and framework for prioritizing improvement actions." (SQA)

"A Maturity Model is a framework that is used as a benchmark for comparison when looking at an organisation's processes." (Experian) [source]

"A means of identifying and/or measuring the maturity of something of interest, such as a Service, Capability, Function, Skill, or Competency." (IF4IT)

06 March 2013

Process Management: Affinity Diagram (Definitions)

"A tool used to gather and group ideas; usually depicted as a “tree” diagram." (Clyde M Creveling, "Six Sigma for Technical Processes: An Overview for R Executives, Technical Leaders, and Engineering Managers", 2006)

"A process workflow model (diagram) showing the flow from one activity to the next." (Toby J Teorey, "Database Modeling and Design" 4th Ed., 2010)

"A form of visualization that shows patterns of ideas or data, by grouping them by topic or some attribute they share." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A group creativity technique that allows large numbers of ideas to be classified into groups for review and analysis." (For Dummies, "PMP Certification All-in-One For Dummies" 2nd Ed., 2013)

"In UML, a diagram that represents work flows for activities. They include several kinds of symbols connected with arrows to show the direction of the work flow." (Rod Stephens, "Beginning Software Engineering", 2015)

"A technique that allows large numbers of ideas to be classified into groups for review and analysis." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK Guide)", 2017)

"A graphical representations of workflows of stepwise activities and actions with support for choice, iteration and concurrency." (IQBBA)

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