🦋Science: On Creativity (Quotes)

"[…] science conceived as resting on mere sense-perception, with no other source of observation, is bankrupt, so far as concerns its claim to self-sufficiency. Science can find no individual enjoyment in nature: Science can find no aim in nature: Science can find no creativity in nature; it finds mere rules of succession. These negations are true of Natural Science. They are inherent in it methodology." (Alfred N Whitehead, "Modes of Thought", 1938)

"The act of discovery escapes logical analysis; there are no logical rules in terms of which a 'discovery machine' could be constructed that would take over the creative function of the genius. But it is not the logician’s task to account for scientific discoveries; all he can do is to analyze the relation between given facts and a theory presented to him with the claim that it explains these facts. In other words, logic is concerned with the context of justification." (Hans Reichenbach, "The Rise of Scientific Philosophy", 1951)

"The design process involves a series of operations. In map design, it is convenient to break this sequence into three stages. In the first stage, you draw heavily on imagination and creativity. You think of various graphic possibilities, consider alternative ways." (Arthur H Robinson, "Elements of Cartography", 1953)

"[…] the difference between creative thinking and unimaginative competent thinking lies in the injection of a some randomness. The randomness must be guided by intuition to be efficient." (John McCarthy et al, "A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence", 1955)

"At each level of complexity, entirely new properties appear. [And] at each stage, entirely new laws, concepts, and generalizations are necessary, requiring inspiration and creativity to just as great a degree as in the previous one." (Herb Anderson, 1972)

"Facts do not ‘speak for themselves’; they are read in the light of theory. Creative thought, in science as much as in the arts, is the motor of changing opinion. Science is a quintessentially human activity, not a mechanized, robot-like accumulation of objective information, leading by laws of logic to inescapable interpretation." (Stephen J Gould, "Ever Since Darwin", 1977)

"Science is not a heartless pursuit of objective information. It is a creative human activity, its geniuses acting more as artists than information processors. Changes in theory are not simply the derivative results of the new discoveries but the work of creative imagination influenced by contemporary social and political forces." (Stephen J Gould, "Ever Since Darwin: Reflections in Natural History", 1977)

"Science, since people must do it, is a socially embedded activity. It progresses by hunch, vision, and intuition. Much of its change through time does not record a closer approach to absolute truth, but the alteration of cultural contexts that influence it so strongly. Facts are not pure and unsullied bits of information; culture also influences what we see and how we see it. Theories, moreover, are not inexorable inductions from facts. The most creative theories are often imaginative visions imposed upon facts; the source of imagination is also strongly cultural." (Stephen J Gould, "The Mismeasure of Man", 1980)

"If intelligence is a capacity that is gradually acquired as a result of development and learning, then a machine that can learn from experience would have, at least in theory, the capacity to carry out intelligent behavior. [...] Humans have created machines that imitate us - that provide mirrors to see ourselves and measure our strength, our intellect, and even our creativity." (Diego Rasskin-Gutman, "Chess Metaphors: Artificial Intelligence and the Human Mind", 2009)

"Some methods, such as those governing the design of experiments or the statistical treatment of data, can be written down and studied. But many methods are learned only through personal experience and interactions with other scientists. Some are even harder to describe or teach. Many of the intangible influences on scientific discovery - curiosity, intuition, creativity - largely defy rational analysis, yet they are often the tools that scientists bring to their work." (Committee on the Conduct of Science, "On Being a Scientist", 1989)

"All of engineering involves some creativity to cover the parts not known, and almost all of science includes some practical engineering to translate the abstractions into practice." (Richard W Hamming, "The Art of Probability for Scientists and Engineers", 1991)

"Good engineering is not a matter of creativity or centering or grounding or inspiration or lateral thinking, as useful as those might be, but of decoding the clever, even witty, messages the solution space carves on the corpses of the ideas in which you believed with all your heart, and then building the road to the next message." (Fred Hapgood, "Up the infinite Corridor: MIT and the Technical Imagination", 1993)

"Indeed, knowledge that one will be judged on some criterion of ‘creativeness’ or ‘originality’ tends to narrow the scope of what one can produce (leading to products that are then judged as relatively conventional); in contrast, the absence of an evaluations seems to liberate creativity." (Howard Gardner, "Creating Minds", 1993)

"[…] creativity is the ability to see the obvious over the long term, and not to be restrained by short-term conventional wisdom." (Arthur J Birch, "To See the Obvious", 1995)

"The pursuit of science is more than the pursuit of understanding. It is driven by the creative urge, the urge to construct a vision, a map, a picture of the world that gives the world a little more beauty and coherence than it had before." (John A Wheeler, "Geons, Black Holes, and Quantum Foam: A Life in Physics", 1998)

"Simple observation generally gets us nowhere. It is the creative imagination that increases our understanding by finding connections between apparently unrelated phenomena, and forming logical, consistent theories to explain them. And if a theory turns out to be wrong, as many do, all is not lost. The struggle to create an imaginative, correct picture of reality frequently tells us where to go next, even when science has temporarily followed the wrong path." (Richard Morris, "The Universe, the Eleventh Dimension, and Everything: What We Know and How We Know It", 1999)

"Science, and physics in particular, has developed out of the Newtonian paradigm of mechanics. In this world view, every phenomenon we observe can be reduced to a collection of atoms or particles, whose movement is governed by the deterministic laws of nature. Everything that exists now has already existed in some different arrangement in the past, and will continue to exist so in the future. In such a philosophy, there seems to be no place for novelty or creativity." (Francis Heylighen, "The science of self-organization and adaptivity", 2001)

"This spontaneous emergence of order at critical points of instability is one of the most important concepts of the new understanding of life. It is technically known as self-organization and is often referred to simply as ‘emergence’. It has been recognized as the dynamic origin of development, learning and evolution. In other words, creativity - the generation of new forms - is a key property of all living systems. And since emergence is an integral part of the dynamics of open systems, we reach the important conclusion that open systems develop and evolve. Life constantly reaches out into novelty." (Fritjof  Capra, "The Hidden Connections", 2002)

"Evolution moves towards greater complexity, greater elegance, greater knowledge, greater intelligence, greater beauty, greater creativity, and greater levels of subtle attributes such as love. […] Of course, even the accelerating growth of evolution never achieves an infinite level, but as it explodes exponentially it certainly moves rapidly in that direction." (Ray Kurzweil, "The Singularity is Near", 2005)

"An ecology provides the special formations needed by organizations. Ecologies are: loose, free, dynamic, adaptable, messy, and chaotic. Innovation does not arise through hierarchies. As a function of creativity, innovation requires trust, openness, and a spirit of experimentation - where random ideas and thoughts can collide for re-creation." (George Siemens, "Knowing Knowledge", 2006)

"Learning emerges from discovery, not directives; reflection, not rules; possibilities, not prescriptions; diversity, not dogma; creativity and curiosity, not conformity and certainty; and meaning, not mandates." (Stephanie P Marshall, "The Power to Transform: Leadership That Brings Learning and Schooling to Life", 2006)

"Systemic problems trace back in the end to worldviews. But worldviews themselves are in flux and flow. Our most creative opportunity of all may be to reshape those worldviews themselves. New ideas can change everything." (Anthony Weston, "How to Re-Imagine the World", 2007)

"In an information economy, entrepreneurs master the science of information in order to overcome the laws of the purely physical sciences. They can succeed because of the surprising power of the laws of information, which are conducive to human creativity. The central concept of information theory is a measure of freedom of choice. The principle of matter, on the other hand, is not liberty but limitation- it has weight and occupies space." (George Gilder, "Knowledge and Power: The Information Theory of Capitalism and How it is Revolutionizing our World", 2013)

"Imagination, as well as reason, is necessary to perfection in the philosophical mind. A rapidity of combination, a power of perceiving analogies, and of comparing them by facts, is the creative source of discovery." (Sir Humphry Davy)

Knowledge Representation: On Data, Information, Knowledge, Wisdom (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)

"It is not enough to observe, experiment, theorize, calculate and communicate; we must also argue, criticize, debate, expound, summarize, and otherwise transform the information that we have obtained individually into reliable, well established, public knowledge." (John M Ziman, "Information, Communication, Knowledge", Nature Vol. 224 (5217), 1969)

"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)

🏷️Knowledge Representation: On Wisdom (Quotes)

"Things […] are some of them continuous […] which are properly and peculiarly called 'magnitudes'; others are discontinuous, in a side-by-side arrangement, and, as it were, in heaps, which are called 'multitudes', a flock, for instance, a people, a heap, a chorus, and the like. Wisdom, then, must be considered to be the knowledge of these two forms. Since, however, all multitude and magnitude are by their own nature of necessity infinite - for multitude starts from a definite root and never ceases increasing; and magnitude, when division beginning with a limited whole is carried on, cannot bring the dividing process to an end […] and since sciences are always sciences of limited things, and never of infinites, it is accordingly evident that a science dealing with magnitude […] or with multitude […] could never be formulated. […] A science, however, would arise to deal with something separated from each of them, with quantity, set off from multitude, and size, set off from magnitude." (Nicomachus of Gerasa, "Introductio Arithmetica", cca. 100 AD)

"[Intuitive] Understanding is consequent upon deliberation, and firmly embraces the better part. For [intuitive] understanding concerns itself with divine truths, and the relish, love, and observance of the latter constitutes true wisdom. Rather than being the [mere] product of nature, these successive steps are the result of grace. The latter, according to its own free determination, derives the various rivulets of the sciences and wisdom from the fountainhead of sense perception. Grace reveals hidden divine truths by means of those things which have been made, and by that unity which belongs to love, communicates what it has made manifest, thus uniting man to God." (John of Salisbury, "Metalogicon", 1159

"Of all things the most desirable is wisdom, whose fruit consists in the love of what is good and the practice of virtue. Consequently the human mind must apply itself to the quest of wisdom, and thoroughly study and investigate questions in order to formulate clear and sound judgments concerning each." (John of Salisbury, "Metalogicon", 1159)

"There can only be one wisdom. For if it were possible that there be several wisdoms, then these would have to be from one. Namely, unity is prior to all plurality." (Nicholas of Cusa, "De Pace Fidei" ["The Peace of Faith"], 1453)

"Our wisdom and deliberation for the most part follow the lead of chance." (Michel de Montaigne, "Essays", 1580)

"Look round the world: contemplate the whole and every part of it: You will find it to be nothing but one great machine, subdivided into an infinite number of lesser machines, which again admit of subdivisions, to a degree beyond what human senses and faculties can trace and explain. All these various machines, and even their most minute parts, are adjusted to each other with an accuracy, which ravishes into admiration all men, who have ever contemplated them. The curious adapting of means to ends, throughout all nature, resembles exactly, though it much exceeds, the productions of human contrivance; of human design, thought, wisdom, and intelligence." (David Hume, "Dialogues Concerning Natural Religion Dialogues Concerning Natural Religion", 1779)

"It should be noted that the seeds of wisdom that are to bear fruit in the intellect are sown less by critical studies and learned monographs than by insights, broad impressions, and flashes of intuition." (Carl von Clausewitz, "On War", 1832)

"Religion is the metaphysics of the masses […] Just as they have popular poetry, and the popular wisdom of proverbs, so they must have popular metaphysics too: for mankind absolutely needs an interpretation of life; and this, again, must be suited to popular comprehension." (Arthur Schopenhauer, "The Horrors and Absurdities of Religion", 1851)

“We learn wisdom from failure much more than from success. We often discover what will do, by finding out what will not do; and probably he who never made a mistake never made a discovery.” (Samuel Smiles, “Facilities and Difficulties”, 1859)

"Collective wisdom, alas, is no adequate substitute for the intelligence of individuals. Individuals who opposed received opinions have been the source of all progress, both moral and intellectual. They have been unpopular, as was natural." (Bertrand Russell, "Why I Am Not a Christian", 1927)

"Accidental discoveries of which popular histories of science make mention never happen except to those who have previously devoted a great deal of thought to the matter. Observation unilluminated by theoretic reason is sterile. […] Wisdom does not come to those who gape at nature with an empty head. Fruitful observation depends not as Bacon thought upon the absence of bias or anticipatory ideas, but rather on a logical multiplication of them so that having many possibilities in mind we are better prepared to direct our attention to what others have never thought of as within the field of possibility." (Morris R Cohen, "Reason and Nature", 1931)

"[…] that all science is merely a game can be easily discarded as a piece of wisdom too easily come by. But it is legitimate to enquire whether science is not liable to indulge in play within the closed precincts of its own method. Thus, for instance, the scientist’s continuous penchant for systems tends in the direction of play." (Johan Huizinga, "Homo Ludens", 1938)

"Wisdom is your perspective on life, your sense of balance, your understanding of how the various parts and principles apply and relate to each other." (Stephen R Covey, "The 7 Habits of Highly Effective People", 1989)

“[…] the human brain must work in models. The trick is to have your brain work better than the other person’s brain because it understands the most fundamental models: ones that will do most work per unit. If you get into the mental habit of relating what you’re reading to the basic structure of the underlying ideas being demonstrated, you gradually accumulate some wisdom."  (Charles T Munger, “Poor Charlie’s Almanack”, 2005)

"The fact that cognitive diversity matters does not mean that if you assemble a group of diverse but thoroughly uninformed people, their collective wisdom will be smarter than an expert's. But if you can assemble a diverse group of people who possess varying degrees of knowledge and insight, you're better off entrusting it with major decisions rather than leaving them in the hands of one or two people, no matter how smart those people are." (James Surowiecki, "The Wisdom of Crowds", 2005)

"[…] many-model thinking produces wisdom through a diverse ensemble of logical frames. The various models accentuate different causal forces. Their insights and implications overlap and interweave. By engaging many models as frames, we develop nuanced, deep understandings." (Scott E Page, "The Model Thinker", 2018)

"A ray of imagination or of wisdom may enlighten the universe, and glow into remotest centuries." (George Berkeley)

"Collective intelligence is where the whole is smarter than any one individual in it. You can think of it that in a predictive context, this could be the wisdom of crowds, sort of thing where people guessing the weight of a steer, the crowd’s guess is going to be better than the average guess of the person in it." (Scott E Page [interview])

"Common sense in an uncommon degree is what the world calls wisdom." (Samuel T Coleridge)

"It is not in the nature of things for any one man to make a sudden violent discovery; science goes step by step, and every man depends on the work of his predecessors. When you hear of a sudden unexpected discovery - a bolt from the blue, as it were - you can always be sure that it has grown up by the influence of one man on another, and it is this mutual influence which makes the enormous possibility of scientific advance. Scientists are not dependent on the ideas of a single man, but on the combined wisdom of thousands of men, all thinking of the same problem, and each doing his little bit to add to the great structure of knowledge which is gradually being erected." (Ernest Rutherford)

"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 highest wisdom has but one science-the science of the whole-the science explaining the whole creation and man's place in it." (Lev N Tolstoy)

🏷️Knowledge Representation: On Data (Quotes)

"Mathematicians obtain the solution of a problem by the mere arrangement of data, and by reducing their reasoning to such simple steps, to conclusions so very obvious, as never to lose sight of the evidence which guides them." (Antoine Lavoisier, "Elements of Chemistry In a New Systematic Order". 1790)

"Before anything can be reasoned upon to a conclusion, certain facts, principles, or data, to reason from, must be established, admitted, or denied." (Thomas Paine, "Rights of Man", 1791)

"The modern age has a false sense of superiority because of the great mass of data at its disposal. But the valid criterion of distinction is rather the extent to which man knows how to form and master the material at his command." (Johann Wolfgang von Goethe, "On Theory of Color", 1810)

"The errors which arise from the absence of facts are far more numerous and more durable than those which result from unsound reasoning respecting true data." (Charles Babbage, "On the Economy of Machinery and Manufactures", 1832)

"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)

"It usually happens in scientific progress, that when a great fact is at length discovered, it approves itself at once to all competent judges. It furnishes a solution to so many problems, and harmonizes with so many other facts, - that all the other data as it were crystallize at once about it." (Edward Everett, "The Uses of Astronomy", [An Oration Delivered at Albany] 1856)

"The ignoring of data is, in fact, the easiest and most popular mode of obtaining unity in one's thought." (William James, "The Sentiment of Rationality", Mind Vol. 4, 1879)

"It is a capital mistake to theorise before one has data." (Arthur C Doyle, "The Adventures of Sherlock Holmes", 1892)

"Physical research by experimental methods is both a broadening and a narrowing field. There are many gaps yet to be filled, data to be accumulated, measurements to be made with great precision, but the limits within which we must work are becoming, at the same time, more and more defined." (Elihu Thomson, "Annual Report of the Board of Regents of the Smithsonian Institution", 1899)

"The data with which any scientific inquiry has to do are trivialities in some other bearing than that one in which they are of account." (Thorstein Veblen, "The Place of Science in Modern Civilisation and Other Essays", 1906)

"The first step in beginning the scientific study of a problem is to collect the data, which are or ought to be 'facts'." (John A Thomson, "Introduction to Science", 1911)

"The man of science, by virtue of his training, is alone capable of realising the difficulties - often enormous - of obtaining accurate data upon which just judgment may be based." (Sir Richard Gregory, "Discovery; or, The Spirit and Service of Science", 1918)

"Philosophy, like science, consists of theories or insights arrived at as a result of systemic reflection or reasoning in regard to the data of experience. It involves, therefore, the analysis of experience and the synthesis of the results of analysis into a comprehensive or unitary conception. Philosophy seeks a totality and harmony of reasoned insight into the nature and meaning of all the principal aspects of reality." (Joseph A Leighton, "The Field of Philosophy: An outline of lectures on introduction to philosophy," 1919)

"A 'poor evaluation' of the probability of anything may reflect ignorance of relevant data which 'ought' to be known. (Clarence I Lewis, "Mind and the World-Order: Outline of a Theory of Knowledge", 1924)

"No human mind is capable of grasping in its entirety the meaning of any considerable quantity of numerical data." (Frank Yates & Ronald Fisher, "Statistical Methods for Research Workers", 1925)

"Take the situation of a scientist solving a problem, where he has certain data, which call for certain responses. Some of this set of data call for his applying such and such a law, while others call for another law." (George H Mead, "Mind, Self, and Society", 1934)

"The laws of science are the permanent contributions to knowledge - the individual pieces that are fitted together in an attempt to form a picture of the physical universe in action. As the pieces fall into place, we often catch glimpses of emerging patterns, called theories; they set us searching for the missing pieces that will fill in the gaps and complete the patterns. These theories, these provisional interpretations of the data in hand, are mere working hypotheses, and they are treated with scant respect until they can be tested by new pieces of the puzzle." (Edwin P Whipple, "Experiment and Experience", [Commencement Address, California Institute of Technology] 1938)

"Not even the most subtle and skilled analysis can overcome completely the unreliability of basic data." (Roy D G Allen, "Statistics for Economists", 1951)

"When evaluating the reliability and generality of data, it is often important to know the aims of the experimenter. When evaluating the importance of experimental results, however, science has a trick of disregarding the experimenter's rationale and finding a more appropriate context for the data than the one he proposed." (Murray Sidman, "Tactics of Scientific Research", 1960)

"Philosophers of science have repeatedly demonstrated that more than one theoretical construction can always be placed upon a given collection of data." (Thomas Kuhn, "The Structure of Scientific Revolutions", 1962) 

"We must include in any language with which we hope to describe complex data-processing situations the capability for describing data." (Grace Hopper, "Management and the Computer of the Future", 1962)

"Modern science is characterized by its ever-increasing specialization, necessitated by the enormous amount of data, the complexity of techniques and of theoretical structures within every field. Thus science is split into innumerable disciplines continually generating new subdisciplines. In consequence, the physicist, the biologist, the psychologist and the social scientist are, so to speak, encapusulated in their private universes, and it is difficult to get word from one cocoon to the other." (Ludwig von Bertalanffy, "General System Theory", 1968)

"At root what is needed for scientific inquiry is just receptivity to data, skill in reasoning, and yearning for truth. Admittedly, ingenuity can help too." (Willard v O Quine, "The Web of Belief", 1970)

"Statistical methods of analysis are intended to aid the interpretation of data that are subject to appreciable haphazard variability." (David V. Hinkley & David Cox, "Theoretical Statistics", 1974)

"In a way, science might be described as paranoid thinking applied to Nature: we are looking for natural conspiracies, for connections among apparently disparate data." (Carl Sagan, "The Dragons of Eden", 1977)

"If we gather more and more data and establish more and more associations, however, we will not finally find that we know something. We will simply end up having more and more data and larger sets of correlations." (Kenneth N Waltz, "Theory of International Politics Source: Theory of International Politics", 1979)

"There is a tendency to mistake data for wisdom, just as there has always been a tendency to confuse logic with values, intelligence with insight. Unobstructed access to facts can produce unlimited good only if it is matched by the desire and ability to find out what they mean and where they lead." (Norman Cousins, "Human Options : An Autobiographical Notebook", 1981) 

"Data in isolation are meaningless, a collection of numbers. Only in context of a theory do they assume significance […]" (George Greenstein, "Frozen Star", 1983)

"Data is raw. It simply exists and has no significance beyond its existence (in and of itself). It can exist in any form, usable or not. It does not have meaning of itself. In computer parlance, a spreadsheet generally starts out by holding data." (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)

"Intuition becomes increasingly valuable in the new information society precisely because there is so much data." (John Naisbitt, "Re-Inventing the Corporation", 1985)

"The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data." (John Tukey, "Sunset Salvo", The American Statistician Vol. 40 (1), 1986)

"Intuition is the art, peculiar to the human mind, of working out the correct answer from data that is, in itself, incomplete or even, perhaps, misleading." (Isaac Asimov, "Forward the Foundation", 1993)

"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) 

"Paradigms are the most general-rather like a philosophical or ideological framework. Theories are more specific, based on the paradigm and designed to describe what happens in one of the many realms of events encompassed by the paradigm. Models are even more specific providing the mechanisms by which events occur in a particular part of the theory's realm. Of all three, models are most affected by empirical data - models come and go, theories only give way when evidence is overwhelmingly against them and paradigms stay put until a radically better idea comes along." (Lee R Beach, "The Psychology of Decision Making: People in Organizations", 1997)

"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)

"The more data we have, the more likely we are to drown in it." (Nassim N Taleb, "Fooled by Randomness", 2001)

"Data is a fact of life. As time goes by, we collect more and more data, making our original reason for collecting the data harder to accomplish. We don't collect data just to waste time or keep busy; we collect data so that we can gain knowledge, which can be used to improve the efficiency of our organization, improve profit margins, and on and on. The problem is that as we collect more data, it becomes harder for us to use the data to derive this knowledge. We are being suffocated by this raw data, yet we need to find a way to use it." (Seth Paul et al. "Preparing and Mining Data with Microsoft SQL Server 2000 and Analysis", 2002)

"Good communication is not just data transfer. You need to show people something that addresses their anxieties, that accepts their anger, that is credible in a very gut-level sense, and that evokes faith in the vision." (John Kotter, "The Heart of Change: Real-Life Stories of How People Change Their Organizations", 2002) 

"Thought, without the data on which to structure that thought, leads nowhere." (Victor J Stenger, "Has Science Found God?: The Latest Results in the Search for Purpose in the Universe", 2003)

"The best scientists aren't the ones who know the most data; they're the ones who know what they're looking for." (Noam Chomsky, [Guardian] 2005)

"Perception requires imagination because the data people encounter in their lives are never complete and always equivocal. [...] 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", 2008)

"Finding patterns is easy in any kind of data-rich environment; that's what mediocre gamblers do. The key is in determining whether the patterns represent signal or noise." (Nate Silver, "The Signal and the Noise: Why So Many Predictions Fail-but Some Don't", 2012)

"The inherent nature of complexity is to doubt certainty and any pretense to finite and flawless data. Put another way, under uncertainty principles, any attempt by political systems to 'impose order' has an equal chance to instead 'impose disorder'." (Lawrence K Samuels, "Defense of Chaos: The Chaology of Politics, Economics and Human Action", 2013)

"The value of having numbers - data - is that they aren't subject to someone else's interpretation. They are just the numbers. You can decide what they mean for you." (Emily Oster, "Expecting Better", 2013)

"A study that leaves out data is waving a big red flag. A decision to include orxclude data sometimes makes all the difference in the world. This decision should be based on the relevance and quality of the data, not on whether the data support or undermine a conclusion that is expected or desired." (Gary Smith, "Standard Deviations", 2014)

"Another way to secure statistical significance is to use the data to discover a theory. Statistical tests assume that the researcher starts with a theory, collects data to test the theory, and reports the results - whether statistically significant or not. Many people work in the other direction, scrutinizing the data until they find a pattern and then making up a theory that fits the pattern." (Gary Smith, "Standard Deviations", 2014)

"Data clusters are everywhere, even in random data. Someone who looks for an explanation will inevitably find one, but a theory that fits a data cluster is not persuasive evidence. The found explanation needs to make sense and it needs to be tested with uncontaminated data." (Gary Smith, "Standard Deviations", 2014)

"Data without theory can fuel a speculative stock market bubble or create the illusion of a bubble where there is none. How do we tell the difference between a real bubble and a false alarm? You know the answer: we need a theory. Data are not enough. […] Data without theory is alluring, but misleading." (Gary Smith, "Standard Deviations", 2014)

"If somebody ransacks data to find a pattern, we still need a theory that makes sense. On the other hand, a theory is just a theory until it is tested with persuasive data." (Gary Smith, "Standard Deviations", 2014)

"Self-selection bias occurs when people choose to be in the data - for example, when people choose to go to college, marry, or have children. […] Self-selection bias is pervasive in 'observational data', where we collect data by observing what people do. Because these people chose to do what they are doing, their choices may reflect who they are. This self-selection bias could be avoided with a controlled experiment in which people are randomly assigned to groups and told what to do." (Gary Smith, "Standard Deviations", 2014)

"These practices - selective reporting and data pillaging - are known as data grubbing. The discovery of statistical significance by data grubbing shows little other than the researcher’s endurance. We cannot tell whether a data grubbing marathon demonstrates the validity of a useful theory or the perseverance of a determined researcher until independent tests confirm or refute the finding. But more often than not, the tests stop there. After all, you won’t become a star by confirming other people’s research, so why not spend your time discovering new theories? The data-grubbed theory consequently sits out there, untested and unchallenged." (Gary Smith, "Standard Deviations", 2014)

"We naturally draw conclusions from what we see […]. We should also think about what we do not see […]. The unseen data may be just as important, or even more important, than the seen data. To avoid survivor bias, start in the past and look forward." (Gary Smith, "Standard Deviations", 2014)

"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)

♾️Cognitive Science: On Crowds (Quotes)

"We are more wicked together than separately. If you are forced to be in a crowd, then most of you should withdraw into your self." (Seneca , cca. 65 AD) 

"The vulgar crowd always is taken by appearances, and the world consists chiefly of the vulgar." (Niccolò Machiavelli, "The Prince", 1513)

"The crowd plays the tyrant, when it is not in fear." (Baruch Spinoza , 1677)

"Public is a ferocious beast: one must chain it up or flee from it." (Voltaire , 1748)

"Every numerous assembly is mob, let the individuals who compose it be what they will." (Lord Chesterfield , 1751) 

"The pretence of collective wisdom is the most palatable of all impostures." (William Godwin, 1793)

"It is easy in the world to live after the world’s opinion; it is easy in solitude to live after our own; but the great man is he who in the midst of the crowd keeps with perfect sweetness the independence of solitude." (Ralph  Emerson, 1840)

"Men, it has been well said, think in herds. It will be seen that they go mad in herds, while they only recover their senses slowly, and one by one." (Charles Mackay, "Extraordinary Popular Delusions and the Madness of Crowds", 1841)

"A mob is a society of bodies voluntarily bereaving themselves of reason." (Ralph W Emerson , 1841) and 

"The nose of a mob is its imagination. By this, at any time, it can be quietly led." (Edgar A Poe, "The Works of Edgar Allan Poe", 1849)

"Those who know that they are profound strive for clarity. Those who would like to seem profound to the crowd strive for obscurity. For the crowd believes that if it cannot see to the bottom of something it must be profound. It is so timid and dislikes going into the water."(Friedrich Nietzsche, "The Gay Science: With a Prelude in Rhymes and an Appendix of Songs", 1882)

"The larger the mob, the greater the apparent anarchy, the more perfect is its sway. It is the supreme law of unreason." (Sir Francis Galton, 1889)

"Good sense travels on the well-worn paths; genius, never. And that is why the crowd, not altogether without reason, is so ready to treat great men as lunatics." (Cesare Lombroso, "The Man of Genius", 1891) 

"If there is a look of human eyes that tells of perpetual loneliness, so there is also the familiar look that is the sign of perpetual crowds." (Alice Meynell, "The Spirit of Place, and Other Essays", 1899)

"Where there had been only jeers or taunts at first, crowds come to listen with serious and sympathetic men." (Edward Carpenter, "My days and dreams: being autobiographical notes", 1916)

"The masses […] neither should nor can direct their personal existence, and still less to rule society in general." (José Ortega y Gasset , 1930) 

"When everything is connected to everything in a distributed network, everything happens at once. When everything happens at once, wide and fast moving problems simply route around any central authority. Therefore overall governance must arise from the most humble interdependent acts done locally in parallel, and not from a central command.A mob can steer itself, and in the territory of rapid, massive, and heterogeneous change, only a mob can steer. To get something from nothing, control must rest at the bottom within simplicity. " (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995)

"Crowds can push the merely good to unearned fame, but they’ll rarely get wholeheartedly behind the terrible." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)

"Beauty is not defined by the masses but by the opinion of the individual." (Rune Leknes)

"Business today consists in persuading crowds." (T.S. Eliot)  

"Crowds are somewhat like the sphinx of ancient fable: It is necessary to arrive at a solution of the problems offered by their psychology or to resign ourselves to being devoured by them." (Gustave Le Bon)

"Educate and inform the whole mass of the people [...] they are the only sure reliance for the preservation of our liberty." (Thomas Jefferson)

"I much prefer the sharpest criticism of a single intelligent man to the thoughtless approval of the masses." (Johann Kepler) 

"In solitude the lonely man is eaten up by himself, among crowds by the many." (Friedrich Nietzsche)

 "It is proof of a base and low mind for one to wish to think with the masses or majority, merely because the majority is the majority. Truth does not change because it is, or is not, believed by a majority of the people." (Giordano Bruno) 

 "If it has to choose who is to be crucified, the crowd will always save Barabbas." (Jean Cocteau)

"In almost every act of our lives whether in the sphere of politics or business in our social conduct or our ethical thinking, we are dominated by the relatively small number of persons who understand the mental processes and social patterns of the masses. It is they who pull the wires that control the public mind." (Edward L. Bernays)

"[It] is impossible for us to establish a living vital connection with the masses unless we will work for them, through them and in their midst, not as their patrons but as their servants." (Gandhi)

 "Men whose counsels you would not take as individuals lead you with ease in a crowd." (Cato)

 "Non-cooperation is an attempt to awaken the masses, to a sense of their dignity and power. This can only be done by enabling them to realize that they need not fear brute force, if they would but know the soul within." (Gandhi)

 "Observe the masses and do the opposite." (James Caan)

"Only those who leisurely approach that which the masses are busy about can be busy about that which the masses take leisurely." (Lao Tzu)

 "Opinions are formed in a process of open discussion and public debate, and where no opportunity for the forming of opinions exists, there may be moods, moods of the masses and moods of individuals, the latter no less fickle and unreliable than the former, but no opinion." (Hannah Arendt)

 "Quotes are empty and meaningless. It is how they are used that gives them purpose, how the person repeating those words gives them meaning. Good quotes do not offer the author immortality. Instead, they give the author limitless rebirths on the tongues of the masses." (Andy Clark) 

 ‎"Two’s a company, three’s a crowd" (saying)

 "The adjustment of reality to the masses and of the masses to reality is a process of unlimited scope, as much for thinking as for perception." (Walter Benjamin)

 "The average man's opinions are much less foolish than they would be if he thought for himself." (Bertrand Russell) 

‎ "The only certainty about following the crowd is that you will all get there together." (Mychal Wynn)

"The man who follows the crowd will usually get no further than the crowd. The man who walks alone is likely to find himself in places no one has ever been." (Alan Ashley-Pitt)

"The mob has many heads but no brains." (Thomas Fuller)

"The wisdom of the masses is not always [...] wise [...]" (Jon Stewart) 

"Truth happens to individuals, not to crowds." (Osho)

"We should not listen to those who like to affirm that the voice of the people is the voice of God, for the tumult of the masses is truly close to madness." (Alcuin, Letter to Charlemagne)

‎"What if the 'wisdom of crowds' turns out to be the ignorance of the masses? In fact, what if the Internet is a 'really bad thing' for the world and its population?" (Stephen Saunders)

 "When a hundred men stand together, each of them loses his mind and gets another one." (Friedrich Nietzsche)

"When distant and unfamiliar and complex things are communicated to great masses of people, the truth suffers a considerable and often a radical distortion. The complex is made over into the simple, the hypothetical into the dogmatic, and the relative into an absolute." (Walter Lippmann)

  

🔖Knowledge Representation: DIKW (Part I: An Introduction)

Collocations like “Web of data”, “Web of Information” “Web of Knowledge” “Data Management”, “Information Management”, “Knowledge Management”, “Data Technologies”, “Information Technologies”, “Knowledge Technologies” and other similar such compounds involving Data, Information and Knowledge (DIK) are increasingly and interchangeably used in various contexts by vendors, customers, researchers and bloggers, sometimes being misused from confusion or exaggeration. On the other side it is true that the border between data, information and knowledge can be shallow, and from here rise up divergent opinions and theories, and as always people like to fight about their ideas and believes. To the three adds wisdom forming what is known as DIKW, the Knowledge Pyramid, however wisdom is less met in the technical landscape presumptively because it’s harder to express and quantify.

DIKW reveals the layered evolution of information from data to knowledge and further to wisdom; it’s just a wide accepted model, a pyramidal representation to which there were attempts of including proto-facts and facts [2], understanding [1] [6], transaction and intuition [7], vision and “One Mindness” [6], and probably other similar attempts might be there in the deep web. Sometimes such theories are pure philosophy apparently without applicability and quite far away from the work of scientists who are used to juggle with data, information and knowledge, relatively easy to quantify and grasp compared to wisdom, intuition, meaning, creativity, vision, consciousness, awareness or any other similar terms that made, since ancient times, philosophers’ delight. 

On the other side the scientific work is built upon the philosophic work, and seemingly as new advancements are made the “New Age” philosophies tend to be integrated in scientific work. From the concepts from the second group, only meaning has started to stir up researcher’s attention, and this mainly in AI domain, which attempts to bridge the gap between humans and machines. I suppose there are attempts also in the area of creativity, vision, intuition or wisdom, though it will be difficult to do concludent steps until the barriers of meaning are not broken.

Data is considered to be “simple isolated facts” [4], a combination of "symbols or isolated and non-interpreted facts" [5], symbols, raw that “simply exists and has no significance beyond its existence” [10], quantified or qualified symbol sets, signals or sensory stimuli perceived [3], etc. Be it facts, symbols, events, signals or sensory stimuli, it is highlighted their isolated and not-interpretable characteristics. When we think of data we refer mainly to the written symbols, independent on whether they have or not meaning for us – a digit or set of digits, a letter and the words they form, an image or any combination of them. In a apparently collection of signs, each sign could be regarded as a data chunk, though it happens that we decipher patterns of signs that we know, for example words, phone numbers, addresses, coordinates, time, etc. In database terminology data refers to a matrix structure (columns vs. records) in which each cells of the matrix contains a data chunk that nowadays could be any aggregation of signs and data types a database system supports. 

 As we can see interpretations of data could have different granularity dependent on the form of aggregation and purpose, thus a natural question: when could we discuss about information? For sure a collection of data is not information, then what ingredient(s) is/are essential in having a chunk of information? I believe that there are two magic words – relation and meaning, actually meaningful relation. Using various algorithms, and even from a simple review of the data, researchers could establish various relations between two data chunks, for example that they always occur together, that one causes the other, that XYZ is the address of John Smith, and so on. 

To make it even more complicated, for an IT professional, a structure, and I’m referring here mainly to databases, supposes already the existence of relations between data, thus statements like XYZ is the address of John Smith who was born on 1st of July and works for ABC are already available. Of course, only few relations are useful, just because two chunks of data occur together, in one or several locations, this doesn’t mean that such a relation is meaningful, while in other situations that might be quite important. 

When we discuss about a meaningful relation we actually imply a context, a multidimensional (mental) frame in which meaning is formed and derived from. Thus a relation could be meaningful in one context and irrelevant in another, and that’s why many say that data don’t equate with information. Discovering that the evolution from data to information is context dependent could maybe solve some of the philosophical disagreements, though this aspect makes it difficult to find a common accepted definition for information. Basically information is just chunks of data found in (meaningful) relation(s).

 In what concerns knowledge things are not less complex, the just formulated definition for information could be adapted from my point of view also to knowledge, advancing the idea that knowledge is information found in meaningful relation. Establishing meaningful relations between information implies a certain level of understanding, conscious or unconscious processing and systematization of information, their integration in the existing mental structures - contexts. Mental structures apply here not only to individuals but also to communities, in the past years the later gaining considerable importance. 

Communities equate with networks, and networked is also the structure of the knowledge, this involving a dynamic (evolutional) nature, with multiple values of truth, levels of organization and granularity. The systematization and integration of knowledge relies on existing or new formed patterns based on characteristics of knowledge. There were written many books about knowledge, trying to depict its characteristics, and there are so many facets that it’s difficult to find a definition that accommodates all the types of knowledge – tacit vs. explicit knowledge, personal vs. networked knowledge, declarative vs. procedural, practical vs. theoretical knowledge, personal vs. collective knowledge, contextual, situational or definitional knowledge, and so on. I find it quite important to understand the various types of characteristics because each of them comes with their own characteristics and uses.

Wisdom is skillful use of knowledge, knowledge put into use, transcended knowledge, understanding the patterns and principles of knowledge, knowing when, where, how, why and by what means to apply the knowledge. Wisdom involves also keeping the balance between the various aspects of situations, strengths and weaknesses altogether, minimizing or totally overcoming biases. In spiritual literature and tradition, wisdom plays a fundamental role, the many books on this topic attempting to reveal the qualities (dimensions) and implications of wisdom. I will limit myself only to give two quotes, namely one from A. Einstein who was remarking that "wisdom is not a product of schooling of the lifelong attempt to acquire it", and B. Russel was remarking that “although our age far surpasses all previous ages in knowledge, there has been no correlative increase in wisdom” [8].

The new added scales to the DIKW pyramid are questionable, it’s kind of a gray area, based maybe on deeper considerations not so easy to grasp, while the lack of definitions and argumentation makes the understanding process even more difficult.  The best example regarding the lack of definitions is the proto-fact, in such situations we could eventually call into help the possible etymological formation. The prefix proto-, from Greek protos, when used in compounds has the meaning of “first” or “before”, thus that proto-facts could be considered as basic/primary facts, maybe axioms, idea that matches also [5]’s view, who’s considering them as assumptions that are used to extract new facts from the world. Following this definition or assumption, proto-facts and facts are rather information, data describing them at most so I really don’t see why the facts and proto-facts are considered as the lower layer on which data layer is based, this because I see data as describing facts, mainly as quantitative or qualitative associations.

From a creationist point of view, everything is vibration, what we perceive is nothing but grossier vibrations taking various forms, some of them recepted and processed by our senses. The layer that comes into contact with the medium (environment) is called by [7] the transaction layer, where the “packets” of sensations are put onto or taken off of the medium, and before any data can exist, the packets have to be received, unpacked and assembled into data. Even if the denomination of transaction layer is not maybe the best, and the description is quite simplistic, this should be at high level the process in which the stimuli from the outside and inside world are transformed by our senses and brain in the so called “data”, forming our continuous reality. [7] believes that somewhere at this level the intuition occurs, though it could be also at higher level as long everything happens within the unconscious mind. Without going to deep into philosophical debate I would limit myself to say that I find well-founded the adding of intuition into DIKW scale, and I could put it on the same level with creativity, innovation, and vision, all three dimensions transcend knowledge and have their important role in understanding and further in wisdom’s attainment. The role of intuition and creative is reinforced also within Edward de Bono’s Six Thinking Hats, red hat representing the intuition, while the green hat, the creativity.

 Vision and “one mindness” seem to come from the New Age vocabulary though they are not so far away from modern science, vision in technical terms is reflected in forecasting, approximating the future based on past trends, while “one mindness” is the principle or the state of art behind Noosphere. It’s true, in what concerns the human being and the actual stage of development, such terms sound to be inapplicable, on the other side when we consider that everything is in continuous evolution/involution, everything is possible. From the point of view of machines (computers), given their interconnectedness and processing power everything is possible.

When we look from a relational point of view, data are symbols with no explicit relation between them, information are data with an explicit relation, knowledge is relational patterns of information, wisdom is patterns of knowledge, intuition is the comprehension of patterns without sensing the patterns consciously, creativity is the discovery or transmutation of new patterns, and maybe it worth to mention also innovation, seen by [9] as the rearranging of relations. More difficult to define from the perspective of relations are the “one mindness” and symbols. The “one mindness” could be eventually regarded as a reflection of the interconnectedness and comprehensions of all existing patterns, including the divine patterns in case of humans. Symbols are at their turn a pattern but of a lower refinement, at form-energetic level. The complexity or relations or patterns denotes the overall complexity, though our senses already hide a higher level of complexity, and most probably here are the barriers of our spiritual and scientific worlds.

In what concerns the meaning, symbols can have or not meaning, or different meanings in different contexts, same could be said about data, information and eventually knowledge, but I would expect that at wisdom and upper levels meaning is fundamental, even conscious or unconscious. With the evolution from data to wisdom and further, the meaning and the relations become richer and more complex. And we can’t discuss about meaning without discussing about context. I tend to believe data have an extrinsic context given by the medium in which they occur, though that’s not necessarily relevant. As per my above given definition, information supposes the existence of a meaningful relation and thus the placement in one or more contexts, while with the integration within a context we could talk already about knowledge.  Probably wisdom acts like a bridge point between contexts, visions extrapolates contexts while in “one mindness” everything becomes one context.

Most of the resources I’ve seen focus mainly on the evolution from data to wisdom, though there is also a feedback mechanism, for example the more high quality data we collect the more are the chances to validate current theories or discover more generalized theories, enriching thus our luggage of information, possibly further evolved to upper layers. It’s interesting also to study the interaction between the various layers, for that having to take into account also the existing theories of learning, of dynamic systems, etc. 

Note:
    I left out understanding from this post because is a complex (philosophical) concept even if everybody has an idea what is about. Please note that I haven’t tried to review the existing DIKW models, but just to write down my thoughts, to create a basis for further posts.

References:
[1] Wikipedia. (2009). DIKW. [Online] Available from: http://en.wikipedia.org/wiki/DIKW (Accessed: 7 May 2009)
[2]  Visual Concept. (1998). Making Meaning. [Online] Available from: http://www.visual-concept.co.uk/makingmeaning.htm (Accessed: 10 February 2009)
[3] Zins, C. (2007). Journal of American Society for Information Science and Technology, 58(4): 279-293, 2007. Wiley InterScience. [Online] Available from: http://www.success.co.il/is/zins_definitions_dik.pdf (Accessed: 16 May 2009)
[4] (Ken) McLennan, K. J.. "Chapter 20 - Knowledge". The Virtual World of Work: How to Gain Competitive
[5] M. J. Coombs ,  H. D. Pfeiffer ,  R. T. Hartley (). e-MGR: an architecture for symbolic plasticity. Int. J. Man-Machine Studies http://www.cs.nmsu.edu/~hdp/PDF/plastic.pdf
[6] OneMind. (2009). Seven Levels of Interaction [Online] Available from: http://onemind.com/2009/12/19/ (Accessed: 7 June 2010)
[7] G. Czerepak. (2007) TIDIKW. [Online] Available from: http://relationary.wordpress.com/2007/07/14/dikw (Accessed: 8 June 2010)
[8] B. Russel. Knowledge and Wisdom
[9] [Online] Available from:  http://thingamy.typepad.com/sigs_blog/2010/01/information-knowledge-wisdom-and-innovation.html (Accessed: 14 June 2010)
[10] G. Bellinger, D. Castro, A. Mills (2004) Data, Information, Knowledge, and Wisdom. [Online] Available from: http://www.systems-thinking.org/dikw/dikw.htm (Accessed: 14 June 2010)