Data Management: Data Culture (Part III: A Tale of Two Cities)

One of the curious things is that as part of their change of culture organizations try to adopt a new language, to give new names to things, try to make distinction between the "AS IS" and "TO BE" states, insisting how the new image will replace the previous one. Occasionally, they even stress how bad things were in the past and how great will be in the future, trying to depict the future in vivid images. 

Even if this might work occasionally, it tends to confuse people and this not necessarily because of the language and the metaphors used, or the fact that same people were in the same positions, but the lack of belief or conviction, respectively half-hearted enthusiasm personified by the parties. To "convert" people to new philosophies one needs to believe in them or mimic that in similar terms. The lack of conviction can easily have a false effect that spreads within the organization. 

Dissociation from the past, from what an organization was, tends to increase the resistance against the new because two different images are involved. On one side there’s the attachment to the past, and even if there were mistakes made, or things didn’t go optimally, the experiences and decisions made are part of the organization, of the people who made them. People as individuals and as an organization should embrace their mistakes and good deeds altogether, learn from them, improve what is to improve and move forward. Conversely, there’s the resistance to the new, to the change, words they don’t believe in yet, the bigger picture is still fuzzy in their minds, and there can be many other reasons that don’t agree with one’s understanding. 

There are images, memories, views, decisions, objectives of the past and people need to recognize the road from what it was to what should be. One can hypothesize that embracing one’s mistake and understanding, the chain of reasoning from then and from now will help an organization transition towards the new. Awareness of one’s situation most probably will help in the transition process. Unfortunately, leaders and technology gurus tend to depict the past as negative, creating thus more negative emotions, respectively reactions in the process. The past is still part of the people, of the organization and will continue to be.

Conversely, the disassociation from the past can create more resistance to the new, and probably more unnecessary barriers. Probably, it’s easier for the gurus to build the new if the past weren’t there! Forgetting the past would be an error because there are many lessons that can be still useful. All the experience needs to be redirected in new directions. It’s more important to help people see the vision of the future, understand their missions, the paths to be followed and the challenges ahead, . 

It sounds more of a rambling from a psychology course, though organizations do have an image they want to change, to bring forth to cope with the various challenges, an image they want to reflect when needed. There are also organizations that want to change but keep their image intact, which leads to deeper conflicts. Unfortunately, changes of image involve conflicts that can become complex from what they bring forth.  

A data culture should increase people’s awareness of the present, respectively of the future, of what it takes to bridge the gap, the challenges ahead, how to embrace change, how to keep a realistic perspective, how to do a reality check, etc. Methodologies can increase people’s awareness and provide the theoretical basis, though walking the path will be a different story for everyone. 

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Data Science: Natural Language Processing (Definitions)

"Using software to 'understand' the meaning contained within texts. Everyday speech is broken down into patterns. Typically, these systems employ syntactic analysis to infer the semantic meaning embedded in documents. NLP identifies patterns in sample texts and makes predictions about unseen texts." (Craig F Smith & H Peter Alesso, "Thinking on the Web: Berners-Lee, Gödel and Turing", 2008)

"Use of computers to interpret and manipulate words as part of a language." (Dougal Hutchison, "Automated Essay Scoring Systems", 2009)

"It is a subfield of Computational Linguistics (i.e. the field that researches linguistics phenomena that occur in digital data), whose focus is on how to build automatic systems able to interpret/generate information in natural language." (Diana Pérez-Marín et al, "Adaptive Computer Assisted Assessment", 2010)

"the notion that the context of text can be inferred from the text itself." (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"An area of computer science involved with the computational study of human languages." (Jason Williamson, "Getting a Big Data Job For Dummies", 2015)

"Similarly to text mining, NLP is a multidisciplinary research field of computer science, artificial intelligence, and linguistics. However, it mainly focuses on the interaction between computers and human languages." (Hamid R Arabnia et al, "Application of Big Data for National Security", 2015)

"Natural Language Processing is prevalently used to analyse the text or speech in order to make machine understand the words like human." (Anumeera Balamurali & Balamurali Ananthanarayanan,"Develop a Neural Model to Score Bigram of Words Using Bag-of-Words Model for Sentiment Analysis", 2020)

 "Natural language processing is the ability of computer program to understand human language as it is spoken or handwritten." (Neha Garg & Kamlesh Sharma, "Machine Learning in Text Analysis", 2020)

"NLP is a field of computer science and linguistics focused on techniques and algorithms for processing data, continuing natural language." (Alex Thomas, "Natural Language Processing with Spark NLP", 2020)

"NLP is a Linguistic approach to interact with human language and computer. This field comes under Artificial Intelligence and Computer Science." (Sayani Ghosal & Amita Jain, "Research Journey of Hate Content Detection From Cyberspace", 2021)

"a field of computer science involved with interactions between computers and human languages." (Analytics Insight)

"is a field of computer science, with the goal to understand or generate human languages, either in text or speech form. There are two primary sub fields of NLP, Natural Language Understanding (NLU), and Natural Language Generation (NLG)." (Accenture)

Systems Engineering: Entropy (Just the Quotes)

"The second law of thermodynamics appears solely as a law of probability, entropy as a measure of the probability, and the increase of entropy is equivalent to a statement that more probable events follow less probable ones." (Max Planck, "A Survey of Physics", 1923)

"True equilibria can occur only in closed systems and that, in open systems, disequilibria called ‘steady states’, or ‘flow equilibria’ are the predominant and characteristic feature. According to the second law of thermodynamics a closed system must eventually attain a time-independent equilibrium state, with maximum entropy and minimum free energy. An open system may, under certain conditions, attain a time-independent state where the system remains constant as a whole and in its phases, though there is a continuous flow of component materials. This is called a steady state. Steady states are irreversible as a whole. […] A closed system in equilibrium does not need energy for its preservation, nor can energy be obtained from it. In order to perform work, a system must be in disequilibrium, tending toward equilibrium and maintaining a steady state, Therefore the character of an open system is the necessary condition for the continuous working capacity of the organism." (Ludwig on Bertalanffy, "Theoretische Biologie: Band 1: Allgemeine Theorie, Physikochemie, Aufbau und Entwicklung des Organismus", 1932)

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

"Every process, event, happening - call it what you will; in a word, everything that is going on in Nature means an increase of the entropy of the part of the world where it is going on. Thus a living organism continually increases its entropy – or, as you may say, produces positive entropy – and thus tends to approach the dangerous state of maximum entropy, which is death. It can only keep aloof from it, i.e. alive, by continually drawing from its environment negative entropy – which is something very positive as we shall immediately see. What an organism feeds upon is negative entropy. Or, to put it less paradoxically, the essential thing in metabolism is that the organism succeeds in freeing itself from all the entropy it cannot help producing while alive." (Erwin Schrödinger, "What is Life?", 1944)

"Time itself will come to an end. For entropy points the direction of time. Entropy is the measure of randomness. When all system and order in the universe have vanished, when randomness is at its maximum, and entropy cannot be increased, when there is no longer any sequence of cause and effect, in short when the universe has run down, there will be no direction to time - there will be no time." (Lincoln Barnett, "The Universe and Dr. Einstein", 1948)

"Just as entropy is a measure of disorganization, the information carried by a set of messages is a measure of organization. In fact, it is possible to interpret the information carried by a message as essentially the negative of its entropy, and the negative logarithm of its probability. That is, the more probable the message, the less information it gives. Clichés, for example, are less illuminating than great poems." (Norbert Wiener, "The Human Use of Human Beings", 1950)

"[…] the characteristic tendency of entropy is to increase. As entropy increases, the universe, and all closed systems in the universe, tend naturally to deteriorate and lose their distinctiveness, to move from the least to the most probable state, from a state of organization and differentiation in which distinctions and forms exist, to a state of chaos and sameness." (Norbert Wiener, "The Human Use of Human Beings", 1950)

"The powerful notion of entropy, which comes from a very special branch of physics […] is certainly useful in the study of communication and quite helpful when applied in the theory of language." (J Robert Oppenheimer, "The Growth of Science and the Structure of Culture", Daedalus 87 (1), 1958) 

"Entropy is a measure of the heat energy in a substance that has been lost and is no longer available for work. It is a measure of the deterioration of a system." (William B. Sill & Norman Hoss (Eds.), "Popular Science Encyclopedia of the Sciences", 1963)

"Suppose we divide the space into little volume elements. If we have black and white molecules, how many ways could we distribute them among the volume elements so that white is on one side and black is on the other? On the other hand, how many ways could we distribute them with no restriction on which goes where? Clearly, there are many more ways to arrange them in the latter case. We measure 'disorder' by the number of ways that the insides can be arranged, so that from the outside it looks the same. The logarithm of that number of ways is the entropy. The number of ways in the separated case is less, so the entropy is less, or the 'disorder' is less." (Richard P Feynman, "Order And Entropy" ["The Feynman Lectures on Physics"], 1964)

"The homeostatic principle does not apply literally to the functioning of all complex living systems, in that in counteracting entropy they move toward growth and expansion." (Daniel Katz, "The Social Psychology of Organizations", 1966)

"Higher, directed forms of energy (e.g., mechanical, electric, chemical) are dissipated, that is, progressively converted into the lowest form of energy, i.e., undirected heat movement of molecules; chemical systems tend toward equilibria with maximum entropy; machines wear out owing to friction; in communication channels, information can only be lost by conversion of messages into noise but not vice versa, and so forth." (Ludwig von Bertalanffy, "Robots, Men and Minds", 1967)

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

"In an isolated system, which cannot exchange energy and matter with the surroundings, this tendency is expressed in terms of a function of the macroscopic state of the system: the entropy." (Ilya Prigogine, "Thermodynamics of Evolution", 1972) 

"There is nothing supernatural about the process of self-organization to states of higher entropy; it is a general property of systems, regardless of their materials and origin. It does not violate the Second Law of thermodynamics since the decrease in entropy within an open system is always offset by the increase of entropy in its surroundings." (Ervin László, "Introduction to Systems Philosophy", 1972)

"Entropy theory, on the other hand, is not concerned with the probability of succession in a series of items but with the overall distribution of kinds of items in a given arrangement." (Rudolf Arnheim, "Entropy and Art: An Essay on Disorder and Order", 1974) 

"The amount of information conveyed by the message increases as the amount of uncertainty as to what message actually will be produced becomes greater. A message which is one out of ten possible messages conveys a smaller amount of information than a message which is one out of a million possible messages. The entropy of communication theory is a measure of this uncertainty and the uncertainty, or entropy, is taken as the measure of the amount of information conveyed by a message from a source. The more we know about what message the source will produce, the less uncertainty, the less the entropy, and the less the information." (John R Pierce, "An Introduction to Information Theory: Symbols, Signals and Noise", 1979) 

"Thus, an increase in entropy means a decrease in our ability to change thermal energy, the energy of heat, into mechanical energy. An increase of entropy means a decrease of available energy." (John R Pierce, "An Introduction to Information Theory: Symbols, Signals and Noise", 1979)

"The third model regards mind as an information processing system. This is the model of mind subscribed to by cognitive psychologists and also to some extent by the ego psychologists. Since an acquisition of information entails maximization of negative entropy and complexity, this model of mind assumes mind to be an open system." (Thaddus E Weckowicz, "Models of Mental Illness", 1984) 

"Disorder increases with time because we measure time in the direction in which disorder increases." (Stephen W Hawking, "The Direction of Time", New Scientist 115 (1568), 1987)

"Somehow, after all, as the universe ebbs toward its final equilibrium in the featureless heat bath of maximum entropy, it manages to create interesting structures." (James Gleick, "Chaos: Making a New Science", 1987)

"Just like a computer, we must remember things in the order in which entropy increases. This makes the second law of thermodynamics almost trivial. Disorder increases with time because we measure time in the direction in which disorder increases."  (Stephen Hawking, "A Brief History of Time", 1988)

"The new information technologies can be seen to drive societies toward increasingly dynamic high-energy regions further and further from thermodynamical equilibrium, characterized by decreasing specific entropy and increasingly dense free-energy flows, accessed and processed by more and more complex social, economic, and political structures." (Ervin László, "Information Technology and Social Change: An Evolutionary Systems Analysis", Behavioral Science 37, 1992) 

"The second law of thermodynamics, which requires average entropy (or disorder) to increase, does not in any way forbid local order from arising through various mechanisms of self-organization, which can turn accidents into frozen ones producing extensive regularities. Again, such mechanisms are not restricted to complex adaptive systems." (Murray Gell-Mann, "What is Complexity?", Complexity Vol 1 (1), 1995)

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

"Contrary to what happens at equilibrium, or near equilibrium, systems far from equilibrium do not conform to any minimum principle that is valid for functions of free energy or entropy production." (Ilya Prigogine, "The End of Certainty: Time, Chaos, and the New Laws of Nature", 1996) 

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

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

"Physical systems are subject to the force of entropy, which increases until eventually the entire system fails. The tendency toward maximum entropy is a movement to disorder, complete lack of resource transformation, and death." (Stephen G Haines, "The Managers Pocket Guide to Systems Thinking & Learning", 1998)

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

"Defined from a societal standpoint, information may be seen as an entity which reduces maladjustment between system and environment. In order to survive as a thermodynamic entity, all social systems are dependent upon an information flow. This explanation is derived from the parallel between entropy and information where the latter is regarded as negative entropy (negentropy). In more common terms information is a form of processed data or facts about objects, events or persons, which are meaningful for the receiver, inasmuch as an increase in knowledge reduces uncertainty." (Lars Skyttner, "General Systems Theory: Ideas and Applications", 2001)

"Emergent self-organization in multi-agent systems appears to contradict the second law of thermodynamics. This paradox has been explained in terms of a coupling between the macro level that hosts self-organization (and an apparent reduction in entropy), and the micro level (where random processes greatly increase entropy). Metaphorically, the micro level serves as an entropy 'sink', permitting overall system entropy to increase while sequestering this increase from the interactions where self-organization is desired." (H Van Dyke Parunak & Sven Brueckner, "Entropy and Self-Organization in Multi-Agent Systems", Proceedings of the International Conference on Autonomous Agents, 2001)

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

"The acquisition of information is a flow from noise to order - a process converting entropy to redundancy. During this process, the amount of information decreases but is compensated by constant recoding. In the recoding the amount of information per unit increases by means of a new symbol which represents the total amount of the old. The maturing thus implies information condensation. Simultaneously, the redundance decreases, which render the information more difficult to interpret." (Lars Skyttner, "General Systems Theory: Ideas and Applications", 2001)

"The function of living matter is apparently to expand the organization of the universe. Here, locally decreased entropy as a result of biological order in existing life is invalidating the effects of the second law of thermodynamics, although at the expense of increased entropy in the whole system. It is the running down of the universe that made the sun and the earth possible. It is the running down of the sun that made life and us possible." (Lars Skyttner, "General Systems Theory: Ideas and Applications", 2001)

"Nature normally hates power laws. In ordinary systems all quantities follow bell curves, and correlations decay rapidly, obeying exponential laws. But all that changes if the system is forced to undergo a phase transition. Then power laws emerge-nature's unmistakable sign that chaos is departing in favor of order. The theory of phase transitions told us loud and clear that the road from disorder to order is maintained by the powerful forces of self-organization and is paved by power laws. It told us that power laws are not just another way of characterizing a system's behavior. They are the patent signatures of self-organization in complex systems." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)

"Entropy is not about speeds or positions of particles, the way temperature and pressure and volume are, but about our lack of information." (Hans C von Baeyer," Information, The New Language of Science", 2003)

"The total disorder in the universe, as measured by the quantity that physicists call entropy, increases steadily steadily as we go from past to future. On the other hand, the total order in the universe, as measured by the complexity and permanence of organized structures, also increases steadily as we go from past to future." (Freeman Dyson, [Page-Barbour lecture], 2004)

"At the foundation of classical thermodynamics are the first and second laws. The first law formulates that the total energy of a system is conserved, while the second law states that the entropy of an isolated system can only increase. The second law implies that the free energy of an isolated system is successively degraded by diabatic processes over time, leading to entropy production. This eventually results in an equilibrium state of maximum entropy. In its statistical interpretation, the direction towards higher entropy can be interpreted as a transition to more probable states." (Axel Kleidon & Ralph D Lorenz, "Entropy Production by Earth System Processes" [in "Non- quilibrium Thermodynamics and the Production of Entropy"], 2005)

"However, the law of accelerating returns pertains to evolution, which is not a closed system. It takes place amid great chaos and indeed depends on the disorder in its midst, from which it draws its options for diversity. And from these options, an evolutionary process continually prunes its choices to create ever greater order."  (Ray Kurzweil, "The Singularity is Near", 2005)

"The second law of thermodynamics states that in an isolated system, entropy can only increase, not decrease. Such systems evolve to their state of maximum entropy, or thermodynamic equilibrium. Therefore, physical self-organizing systems cannot be isolated: they require a constant input of matter or energy with low entropy, getting rid of the internally generated entropy through the output of heat ('dissipation'). This allows them to produce ‘dissipative structures’ which maintain far from thermodynamic equilibrium. Life is a clear example of order far from thermodynamic equilibrium." (Carlos Gershenson, "Design and Control of Self-organizing Systems", 2007)

"We have to be aware that even in mathematical and physical models of self-organizing systems, it is the observer who ascribes properties, aspects, states, and probabilities; and therefore entropy or order to the system. But organization is more than low entropy: it is structure that has a function or purpose." (Carlos Gershenson, "Design and Control of Self-organizing Systems", 2007)

"Heat is the energy of random chaotic motion, and entropy is the amount of hidden microscopic information." (Leonard Susskind, "The Black Hole War", 2008)

"Second Law of thermodynamics is not an equality, but an inequality, asserting merely that a certain quantity referred to as the entropy of an isolated system - which is a measure of the system’s disorder, or ‘randomness’ - is greater (or at least not smaller) at later times than it was at earlier times." (Roger Penrose, "Cycles of Time: An Extraordinary New View of the Universe", 2010) 

"The laws of thermodynamics tell us something quite different. Economic activity is merely borrowing low-entropy energy inputs from the environment and transforming them into temporary products and services of value. In the transformation process, often more energy is expended and lost to the environment than is embedded in the particular good or service being produced." (Jeremy Rifkin, "The Third Industrial Revolution", 2011)

"In a physical system, information is the opposite of entropy, as it involves uncommon and highly correlated configurations that are difficult to arrive at." (César A Hidalgo, "Why Information Grows: The Evolution of Order, from Atoms to Economies", 2015)

"The passage of time and the action of entropy bring about ever-greater complexity - a branching, blossoming tree of possibilities. Blossoming disorder (things getting worse), now unfolding within the constraints of the physics of our universe, creates novel opportunities for spontaneous ordered complexity to arise." (D J MacLennan, "Frozen to Life", 2015)

"Information theory leads to the quantification of the information content of the source, as denoted by entropy, the characterization of the information-bearing capacity of the communication channel, as related to its noise characteristics, and consequently the establishment of the relationship between the information content of the source and the capacity of the channel. In short, information theory provides a quantitative measure of the information contained in message signals and help determine the capacity of a communication system to transfer this information from source to sink over a noisy channel in a reliable fashion." (Ali Grami, "Information Theory", 2016)

"The Second Law of Thermodynamics states that in an isolated system (one that is not taking in energy), entropy never decreases. (The First Law is that energy is conserved; the Third, that a temperature of absolute zero is unreachable.) Closed systems inexorably become less structured, less organized, less able to accomplish interesting and useful outcomes, until they slide into an equilibrium of gray, tepid, homogeneous monotony and stay there." (Steven Pinker, "The Second Law of Thermodynamics", 2017)

"In information theory this notion, introduced by Claude Shannon, is used to express unpredictability of information content. For instance, if a data set containing n items was divided into k groups each comprising n i items, then the entropy of such a partition is H = p 1 log( p 1 ) + … + p k log( p k ), where p i = n i / n . In case of two alternative partitions, the mutual information is a measure of the mutual dependence between these partitions." (Slawomir T Wierzchon, "Ensemble Clustering Data Mining and Databases", 2018) [where i is used as index]

"Entropy is a measure of amount of uncertainty or disorder present in the system within the possible probability distribution. The entropy and amount of unpredictability are directly proportional to each other." ("G Suseela & Y Asnath V Phamila, "Security Framework for Smart Visual Sensor Networks", 2019)

"In the physics [entropy is the] rate of system´s messiness or disorder in a physical system. In the social systems theory - social entropy is a sociological theory that evaluates social behaviors using a method based on the second law of thermodynamics." (Justína Mikulášková et al, "Spiral Management: New Concept of the Social Systems Management", 2020)

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

DBMS: Extensible Markup Language (Definitions)

"A standard for a markup language, similar to HTML, that allows tags to be defined to describe any kind of data you have, making it very popular as a format for data feeds." (Mike Moran & Bill Hunt , "Search Engine Marketing, Inc", 2005)

"Facilitates the assignment of meaningful structures and definitions of data and services for use by multiple systems. XML simplifies the ability to transmit and share data." (Jill Dyché & Evan Levy, "Customer Data Integration: Reaching a Single Version of the Truth", 2006)

"Simple and flexible text format used to represent data. XML was designed by the World Wide Web Consortium (W3C)." (Sara Morganand & Tobias Thernstrom , "MCITP Self-Paced Training Kit : Designing and Optimizing Data Access by Using Microsoft SQL Server 2005 - Exam 70-442", 2007)

"separates content from format, thus letting the browser decide how and where content gets displayed. XML is not a language, but a system for defining other languages so that they understand their vocabulary." (Craig F Smith & H Peter Alesso, "Thinking on the Web: Berners-Lee, Gödel and Turing", 2008)

"A platform-independent markup language for specifying the structure of data in a text document used for both data storage and the transfer of data." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

"A way of representing data and data relationships in text files, typically for data exchange between software of different types." (Jan L Harrington, "SQL Clearly Explained" 3rd Ed. , 2010)

"A metalanguage used to represent and manipulate data elements. Unlike other markup languages, XML permits the manipulation of a document’s data elements. XML is designed to facilitate the exchange of structured documents such as orders and invoices over the Internet." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"A specification for creating text files that contain hierarchical data." (Rod Stephens, "Start Here!™ Fundamentals of Microsoft® .NET Programming", 2011)

"Has been created to overcome some difficulties proper to HTML (Hypertext Markup Language) that – developed as a means for instructing the Web browsers how to display a given Web page – is a ‘presentation-oriented’ markup tool. XML is called ‘extensible’ because, at the difference of HTML, is not characterized by a fixed format, but it lets the user design its own customized markup languages (using, e.g., a specific DTD, Document Type Description) for limitless different types of documents; XML is then a ‘content-oriented’ markup tool." (Gian P Zarri, "RDF and OWL for Knowledge Management", 2011)

"A set of rules for encoding documents electronically. XML was chosen as the standard message format because of its widespread use and open source development efforts." (Mike Harwood, "Internet Security: How to Defend Against Attackers on the Web" 2nd Ed., 2015)

"A standard metalanguage for defining markup languages that is based on Standard Generalized Markup Language (SGML)." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

"Extensible markup language (XML) is a simple, very flexible text format derived from SGML (standard generalized markup language). While XML was originally designed to meet the challenges of large-scale electronic publishing, it plays an increasingly significant role in the exchange of a wide variety of data on the web." (Kamalendu Pal, "Integrating Heterogeneous Enterprise Data Using Ontology in Supply Chain Management", 2019)

"A universal markup language for text and data, using nested tags to add structure and meta-information to the content." (Daniel Leuck et al, "Learning Java" 5th Ed., 2020)

"A 'best practices' subset of SGML that has been designed by the Worldwide Web Consortium (W3C) for use on the Internet." (Microfocus)

"A notation in which you describe the structure of information in a text document by enclosing information in user-defined tags that define the syntactic elements. A flexible way to create common information formats and share both the format and the data on the World Wide Web, intranets, and elsewhere. J2EE deployment descriptors are expressed in XML." (Microfocus)

DBMS: Simple Protocol and RDF Query Language (Definitions)

"A simple query language for accessing RDF structures. As the majority of the query languages developed within a Web context, SPARQL is based on a strict ‘pattern-matching’ approach, which means that no inference facilities are directly associated with SPARQL. As the majority of the Web query languages, SPARQL makes use of a SQL-like format, employing then operators in the style of SELECT and WHERE." (Gian P Zarri, "RDF and OWL for Knowledge Management", 2011)

"An RDF query language standardized by the World Wide Web Consortium (W3C)." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"SPARQL is an RDF query language standardized by the World Wide Web Consortium (W3C). The acronym stands for SPARQL Protocol and RDF Query Language." (Michael Fellmann et al, "Supporting Semantic Verification of Process Models", 2012)

"An RDF query language; its name is a recursive acronym that stands for SPARQL Protocol and RDF Query Language." (Mahdi Gueffaz, "ScaleSem Approach to Check and to Query Semantic Graphs", 2015)

"An SQL-like, RDF query language and a recommendation by W3C, developed to manipulate and query the data stored in RDF format." (T R Gopalakrishnan Nair, "Intelligent Knowledge Systems", 2015)

"Is an RDF query language, that is, a semantic query language for databases, able to retrieve and manipulate data stored in Resource Description Framework format." (Fu Zhang et al, "A Review of Answering Queries over Ontologies Based on Databases", 2016)

"Is an RDF query language, that is, a semantic query language for databases, able to retrieve and manipulate data stored in Resource Description Framework format." (Fu Zhang & Haitao Cheng, "A Review of Answering Queries over Ontologies Based on Databases", 2016)

"SPARQL (Simple Protocol and RDF Query Language) is an RDF query language which is a W3C recommendation. SPARQL contains capabilities for querying required and optional graph patterns along with their conjunctions and disjunctions." (Hairong Wang et al, "Fuzzy Querying of RDF with Bipolar Preference Conditions", 2016)

"SPARQL can be used to express queries across diverse data sources, whether the data is stored natively as RDF or viewed as RDF via middleware. SPARQL contains capabilities for querying required and optional graph patterns along with their conjunctions and disjunctions." (Jingwei Cheng et al, "RDF Storage and Querying: A Literature Review", 2016)

"SPARQL (pronounced 'sparkle', a recursive acronym for SPARQL protocol and RDF query language) is an RDF query language, that is, a semantic query language for databases, able to retrieve and manipulate data stored in resource description framework (RDF) format." (Senthil K Narayanasamy & Dinakaran Muruganantham, "Effective Entity Linking and Disambiguation Algorithms for User-Generated Content (UGC)", 2018)

"SPARQL (Simple Protocol and RDF Query Language) is an RDF query language which is a W3C recommendation. SPARQL contains capabilities for querying required and optional graph patterns along with their conjunctions and disjunctions." (Zongmin Ma & Li Yan, "Towards Massive RDF Storage in NoSQL Databases: A Survey", 2019)

"It is a query language on documents described in RDF." (Antonio Sarasa-Cabezuelo & José Luis Fernández-Vindel, "A Model for the Creation of Academic Activities Based on Visits", 2020)

"The SPARQL query language is a structured language for querying RDF data in a declarative fashion. Its core function is subgraph pattern matching, which corresponds to finding all graph homomorphism in the data graph for a query graph." (Kamalendu Pal, "Ontology-Assisted Enterprise Information Systems Integration in Manufacturing Supply Chain", 2020)

"Query language used to access and retrieve RDF data distributed in different geographical locations." (Janneth Chicaiza, "Leveraging Linked Data in Open Education", 2021)

"It is used for querying data in RDF format, in a similar way that SQL is used to query relational databases. SPARQL is a standard created and maintained by the World Wide Web Consortium. SPARQL is useful for getting data out of linked databases as an alternative to a more specific API." (Data.Gov.UK)

"A query language similar to SQL, used for queries to a linked-data triple store." ("Open Data Handbook")

Software Engineering: Markup Language (Definitions)

"A formal way of annotating a document or collection of digital data using embedded encoding tags to indicate the structure of the document or datafile and the contents of its data elements. This markup also provides a computer with information about how to process and display marked-up documents. HTML, XML, and SGML are examples of standardized markup languages." (J P Getty Trust, "Introduction to Metadata" 2nd Ed., 2008)

"A markup language is used to structure a document’s character data into logical components, and 'name' them in a manner that is useful. These labels (element names) provide either formatting information about how the character data should be visually presented (for a word processor or a web browser, for instance) or they can provide 'semantic' (meaningful) information about what kind of data the component represents. Markup languages provide a simple format for exchanging text-based character data that can be understood by both humans and machines." (Craig F Smith & H Peter Alesso, "Thinking on the Web: Berners-Lee, Gödel and Turing", 2008)

"A way of encoding information that uses plain text containing special tags often delimited by angle brackets (< and >). Specific markup languages are often created, based on XML, to standardize the interchange of information between different computer systems and services. See also XML." (Judith Hurwitz et al, "Service Oriented Architecture For Dummies" 2nd Ed., 2009)

"A set of special codes placed inside a text document to identify the elements of the document and optionally to give instructions to software using the document." (Jan L Harrington, "SQL Clearly Explained" 3rd Ed. , 2010)

"A set of symbols or rules that describe format, structure, or display of a document or file separate from the actual contents." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A mechanism to identify structures in a document." (Charles Cooper & Ann Rockley, "Managing Enterprise Content: A Unified Content Strategy" 2nd Ed., 2012)

"A way of encoding information that uses plain text containing special tags often delimited by angle brackets (< and >). Specific markup languages are based on XML to standardize the interchange of information between different computer systems and services. See also XML." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"A language that uses tags to annotate the information in a document" (Nell Dale & John Lewis, "Computer Science Illuminated, 6th Ed.", 2015)

Software Engineering: Reverse Engineering (Definitions)

"The process of analyzing existing software code and associated documentation to recover its architectural design and specification." (Ian Sommerville, "Software Engineering", 1996)

"The process of analyzing a subject system with two goals in mind: (1) to identify the system’s components and their interrelationships; and, (2) to create representations of the system in another form or at a higher level of abstraction." (Margaret Y Chu, "Blissful Data", 2004)

"Reverse engineering is the process of discovering the functions and their interrelationships of a software system as well as creating representations of the system in another form or at a higher level of abstraction." (Chia-Chu Chiang, "Software Modernization of Legacy Systems for Web Services Interoperability", 2008)

"the construction of a model from a set of source code files." (Bruce P Douglass, "Real-Time Agility: The Harmony/ESW Method for Real-Time and Embedded Systems Development", 2009)

"The process of transforming code into a model through a mapping from a specific implementation language." (Liliana M Favre et al, Foundations for MDA Case Tools", 2009)

[database reverse engineering:] "The process through which the logical and conceptual schemas of a legacy database, or of a set of files, are recovered, or rebuilt, from various information sources such as DDL code, data dictionary contents, database contents, or the source code of application programs that use the database." (Jean-Luc Hainaut et al, "Database Reverse Engineering", 2009)

"The process of transforming the physical schema of any particular database into a logical model." (Paulraj Ponniah, "Data Warehousing Fundamentals for IT Professionals", 2010)

"The process of deriving a draft physical model representing an implemented system (application and/or database) from automated scanning of the implemented application and database objects, as a first step towards redesign." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"The process of discovering the technological principles of a device, object or system through analysis of its structure, function and operation." (Tian Ge & Jianfeng Feng, "Granger Causality: Its Foundation and Applications in Systems Biology", 2011) 

"The process of taking a competitor's product apart and putting it back together again to better understand the manufacturing process and the product design." (Leslie G Eldenburg & Susan K Wolcott, "Cost Management" 2nd Ed., 2011)

"The process of analyzing and comprehending available software artifacts, such as requirements, design, architectures and code in order to extract information and provide high-level views of the system." (Liliana Favre et al, "Reverse Engineering of Object-Oriented Code: An ADM Approach" , 2015)

"It is a process in which a machine is completely dismantled in order to understand the intricacies of the machine. Finally, it is reassembled with added improvisation." Kuldeep K Saxena & Ankita Awasthi, "Novel Additive Manufacturing Processes and Techniques in Industry 4.0", 2020)

"The analysis of a subject system to identify its components and their interrelationships, and to create its representations in another form, or at higher level of abstraction." (Djelloul Bouchiha, "Reengineering Legacy Systems Towards New Technologies", 2021)

Software Engineering: Protocol (Definitions)

"The language or rules and conventions that two computers use to pass messages across a network medium. Networking software generally implements multiple levels of protocols layered one on top of another." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"A set of rules or standards designed to enable computers to connect with one another and exchange information." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"The way in which two computers transfer data between each other." (Greg Perry, "Sams Teach Yourself Beginning Programming in 24 Hours 2nd Ed.", 2001)

"A list of methods that a class must implement to conform or adopt the protocol. Protocols provide a way to standardize an interface across classes." (Stephen G Kochan, "Programming in Objective-C", 2003)

"A set of rules that govern a transaction." (Marcus Green & Bill Brogden, "Java 2™ Programmer Exam Cram™ 2 (Exam CX-310-035)", 2003)

"A set of semantic and syntactic rules that determines the behavior of functions in achieving communication." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"A language and a set of rules that allow computers to interact in a well-defined way. Examples are FTP, HTTP, and NNTP." (Craig F Smith & H Peter Alesso, "Thinking on the Web: Berners-Lee, Gödel and Turing", 2008)

"A specification - often a standard - that describes how computers communicate with each other, for example, the TCP/IP suite of communication protocols or the OAI-PMH." (J P Getty Trust, "Introduction to Metadata" 2nd Ed., 2008)

"To communicate effectively, client applications and database servers need a commonly agreed-upon approach. A protocol is a communication standard adhered to by both parties that makes these conversations possible." (Robert D Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"A set of rules that computers use to establish and maintain communication amongst themselves." (Judith Hurwitz et al, "Service Oriented Architecture For Dummies" 2nd Ed., 2009)

"the forms and ceremony used to manage the interaction of elements." (Bruce P Douglass, "Real-Time Agility: The Harmony/ESW Method for Real-Time and Embedded Systems Development", 2009)

"The rules governing the syntax, semantics, and synchronization of communication." (David Lyle & John G Schmidt, "Lean Integration", 2010)

"A list of methods that a class must implement to conform to or adopt the protocol. Protocols provide a way to standardize an interface across classes. See also formal protocol and informal protocol." (Stephen G Kochan, "Programming in Objective-C" 4th Ed., 2011)

"A set of conventions that govern the communications between processes. Protocol specifies the format and content of messages to be exchanged." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"The standard or set of rules that govern how devices on a network exchange and how they need to function in order to 'talk' to each other." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"A standard set of formats and procedures that enable computers to exchange information." (Microsoft, "SQL Server 2012 Glossary", 2012)

"In networking, an agreed-upon way of sending messages back and forth so that neither correspondent will get too confused." (Jon Orwant et al, "Programming Perl" 4th Ed., 2012)

"A set of guidelines defining network traffic formats for the easy communication of data between two hosts." (Mark Rhodes-Ousley, "Information Security: The Complete Reference, Second Edition, 2nd Ed.", 2013)

"A set of instructions, policies, or fully described procedures for accomplishing a service, operation, or task." (Jules H Berman, "Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information", 2013)

"A set of rules controlling the communication and transfer of data between two or more devices or systems in a communication network." (IBM, "Informix Servers 12.1", 2014)

"A rule or custom that governs how something is done. In a computer context, it refers to a standard for transferring data." (Faithe Wempen, "Computing Fundamentals: Introduction to Computers", 2015)

"A set of rules that defines how data is formatted and processed on a network" (Nell Dale & John Lewis, "Computer Science Illuminated" 6th Ed., 2015)

"Defined policies or standards that users adhere to. Protocols are well-defined and accepted procedures. In computer networking, the term refers to algorithms for exchanging various types of data and their interpretation at origination and destination." (Mike Harwood, "Internet Security: How to Defend Against Attackers on the Web" 2nd Ed., 2015)