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'''Information''' as a concept bears a diversity of meanings, from everyday usage to technical settings. Generally speaking, the concept of information is closely related to notions of [[communication]], [[constraint]], [[control system|control]], [[data]], [[form]], [[instruction]], [[knowledge]], [[meaning]], [[stimulation|mental stimulus]], [[pattern]], [[perception]], and [[knowledge representation|representation]].
  
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{{Infolong}}
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'''Information''' as a [[Conveyed concept|concept]] has many meanings, from everyday usage to technical settings. The concept of information is closely related to notions of [[constraint]], [[communication]], [[control system|control]], [[data]], [[wikt:form|form]], [[instruction]], [[knowledge]], [[Meaning (linguistics)|meaning]], [[stimulation|mental stimulus]], [[pattern]], [[perception]], and [[knowledge representation|representation]]. In its most restricted technical meaning, information is an ordered sequence of symbols.
   
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The English word was apparently derived from the Latin accusative form (informationem) of the nominative (informatio): this noun is in its turn derived from the verb "informare" (to inform) in the sense of "to give form to the mind", "to discipline", "instruct", "teach": "Men so wise should go and inform their kings." (1330) ''Inform'' itself comes (via French) from the Latin verb ''informare'', to give form to, to form an idea of. Furthermore, Latin itself already contained the word ''informatio'' meaning concept or idea, but the extent to which this may have influenced the development of the word ''information'' in English is unclear.
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Many people speak about the [[Information Age]] as the advent of the [[Knowledge Age]] or [[knowledge society]], the [[information society]], and [[Information technology|information technologies]], and even though [[information science]] and [[computer science]] are often in the spotlight, the word "information" is often used without careful consideration of the various meanings it has acquired.
  
   
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As a final note, the ancient Greek word for ''form'' was "μορφή" (morf -> morphe, [[Morph]]) and also ''είδος'' [[eidos]] (kind, idea, shape, set), the latter word was famously used in a technical philosophical sense by [[Plato]] (and later [[Aristotle]]) to denote the ideal identity or essence of something (see [[Theory of forms]]). "Eidos" can also be associated with [[thought]], [[proposition]] or even [[concept]].
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== Information as a message ==
  
   
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== As a message ==
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'''Information''' is the state of a system of interest (curiosity). Message is the information materialized.
  
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Information is a term with many meanings depending on context, but is as a rule closely related to such concepts as meaning, knowledge, instruction, communication, representation, and mental stimulus. Simply stated, information is a [[message]] received and understood. In terms of data, it can be defined as a collection of facts from which conclusions may be drawn. There are many other aspects of information since it is the knowledge acquired through study or experience or instruction. But overall, information is the result of processing, manipulating and organizing data in a way that adds to the knowledge of the person receiving it.
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'''Information''' is the state of a system of interest. Message is the information materialized.
   
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'''Information''' is a [[message]] from a [[sender]] to one or more receivers. If information is viewed in this manner, it does not have to be accurate. It may be a truth or a lie, or just the sound of a kiss. Even a disruptive noise used to inhibit the flow of communication and create misunderstanding would in this view be a form of information. This model assumes there is a definite sender and at least one receiver. Many refinements of the model assume the existence of a common language understood by the sender and at least one of the receivers. An important variation identifies information as that which would be [[communication|communicated]] by a message if it was sent from a sender to a receiver capable of understanding the message. However, in requiring the existence of a definite sender, the "information as a message" model does not attach any significance to the idea that information is something that can be extracted from an environment, e.g., through observation, reading or measurement.
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Information is a quality of a [[message]] from a [[sender]] to one or more receivers. Information is always ''about'' something (size of a parameter, occurrence of an event, value, ethics, etc). Viewed in this manner, information does not have to be accurate; it may be a truth or a lie, or just the sound of a falling tree. Even a disruptive noise used to inhibit the flow of communication and create misunderstanding would in this view be a form of information. However, generally speaking, if the ''amount'' of information in the received message increases, the message is more accurate.
   
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This model assumes there is a definite [[sender]] and at least one receiver. Many refinements of the model assume the existence of a common language understood by the sender and at least one of the receivers. An important variation identifies information as that which would be communicated by a message if it were sent from a sender to a receiver capable of understanding the message. In another variation, it is not required that the sender be capable of understanding the message, or even cognizant that there is a message, making information something that can be extracted from an environment, e.g., through [[observation]], reading or measurement.
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=== Measuring information ===
  
   
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[[Communication theory]] provides a numerical measure of the uncertainty of an outcome. For example, we can say that "the signal contained thousands of bits of information". Communication theory tends to use the concept of [[information entropy]], generally attributed to [[Claude Shannon]], see [[Information#Measuring_information_entropy|below]].
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The view of information as a message came into prominence with the publication in 1948 of an influential paper by [[Claude Shannon]], "[[A Mathematical Theory of Communication]]." This paper provides the foundations of [[information theory]] and endows the word ''information'' not only with a technical meaning but also a measure. If the sending device is equally likely to send any one of a set of <math>N</math> messages, then the preferred measure of "the information produced when one message is chosen from the set" is the base two [[logarithm]] of <math>N</math> (This measure is called '''[[self-information]]'''). In this paper, Shannon continues:
  
   
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Another form of information is [[Fisher information]], a concept of [[R.A. Fisher]]. This is used in application of statistics to [[estimation theory]] and to science in general. Fisher information is thought of as the amount of information that a message carries about an unobservable parameter. It can be computed from knowledge of the [[likelihood function]] defining the system. For example, with a normal likelihood function, the Fisher information is the reciprocal of the variance of the law. In the absence of knowledge of the likelihood law, the Fisher information may be computed from normally distributed score data as the reciprocal of their second moment.
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:''The choice of a logarithmic base corresponds to the choice of a unit for measuring information. If the base 2 is used the resulting units may be called binary digits, or more briefly [[bit]]s, a word suggested by [[John Tukey|J. W. Tukey]]. A device with two stable positions, such as a relay or a flip-flop circuit, can store one bit of information. N such devices can store N bits ...'' [The Bell System Technical Journal, Vol. 27, p. 379, (July 1948).]
  
   
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Even though information and data are often used interchangeably, they are actually very different. Data is a set of unrelated information, and as such is of no use until it is properly evaluated. Upon evaluation, once there is some significant relation between data, and they show some relevance, then they are converted into information. Now this same data can be used for different purposes. Thus, till the data convey some information, they are not useful and therefore not information.
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A complementary way of measuring information is provided by [[Algorithmic information theory]]. In brief, this measures the information content of a list of symbols based on how predictable they are, or more specifically how easy it is to generate the list. The sequence below would have a very low algorithmic information measurement since it is a very predictable pattern, and as the pattern continues the measurement would not change. Shannon information would give the same information measurement for each symbol, since they are [[statistical randomness|statistically random]], and each new symbol would increase the measurement.
  
   
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=== Measuring information entropy ===
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: 123456789101112131415161718192021
  
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The view of information as a message came into prominence with the publication in 1948 of an influential paper by Claude Shannon, "[[A Mathematical Theory of Communication]]." This thesis provides the foundations of [[information theory]] and endows the word ''information'' not only with a technical meaning but also a measure. If the sending device is equally likely to send any one of a set of ''N'' messages, then the preferred measure of "the information produced when one message is chosen from the set" is the base two [[logarithm]] of <math>N</math> (This measure is called ''[[self-information]]''). In this paper, Shannon continues:
   
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{{quotation|The [[choice]] of a logarithmic base corresponds to the choice of a [[units of information|unit for measuring information]]. If the base 2 is used the resulting units may be called binary digits, or more briefly [[bit]]s, a word suggested by [[John Tukey|J. W. Tukey]]. A device with two stable positions, such as a relay or a flip-flop circuit, can store one bit of information. N such devices can store N bits…<ref name = "Shannon">The Bell System Technical Journal, Vol. 27, p. 379, (July 1948).</ref>}}
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It is important to recognise the limitations of Shannon's work from the perspective of human meaning. When referring to the meaning content of a message Shannon noted ''“Frequently the messages have '''meaning”…''' these semantic aspects of communication are irrelevant to the engineering problem. The significant aspect is that the actual message is one selected '''from a set of possible messages'''”'' (emphasis in original).
 
   
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A complementary way of measuring information is provided by [[algorithmic information theory]]. In brief, this measures the information content of a list of symbols based on how predictable they are, or more specifically how easy it is to compute the list through a [[computer program|program]]: the information content of a sequence is the number of bits of the shortest program that computes it. The sequence below would have a very low algorithmic information measurement since it is a very predictable pattern, and as the pattern continues the measurement would not change. Shannon information would give the same information measurement for each symbol, since they are [[statistical randomness|statistically random]], and each new symbol would increase the measurement.
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In Information Theory signals are part of a process, not a substance, they do something, they do not contain any specific meaning. Combining [[Algorithmic information theory]] and Information Theory we can conclude that the most random signal contains the most information as it can be interpreted in any way and cannot be compressed.
  
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:123456789101112131415161718192021
   
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It is important to recognize the limitations of traditional information theory and algorithmic information theory from the perspective of human meaning. For example, when referring to the meaning content of a message Shannon noted “Frequently the messages have ''meaning…'' these semantic aspects of communication are irrelevant to the engineering problem. The significant aspect is that the actual message is one selected ''from a set of possible messages''” (emphasis in original).
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Micheal Reddy noted that ''“signals” of the mathematical theory are “patterns that can be exchanged”. There is no message contained in the signal, the signals covey the ability to select from a set of possible messages.”'' In information theory “the system must be designed to operate for each possible selection, not just the one which will actually be chosen since this is unknown at the time of design.”
 
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See also [[lexicographic information cost]].
  
   
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In information theory signals are part of a process, not a substance; they do something, they do not contain any specific meaning. Combining algorithmic information theory and information theory we can conclude that the most random signal contains the most information as it can be interpreted in any way and cannot be compressed.{{Citation needed|date=August 2007}}
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== Information as a pattern ==
  
   
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Michael Reddy noted that "'signals' of the [[mathematical theory]] are 'patterns that can be exchanged'. There is no message contained in the signal, the signals convey the ability to select from a set of possible messages." In information theory "the system must be designed to operate for each possible selection, not just the one which will actually be chosen since this is unknown at the time of design".
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Information is any represented [[pattern]]. This view assumes neither accuracy nor directly communicating parties, but instead assumes a separation between an object and its representation, as well as the involvement of someone capable of understanding this relationship. This view seems therefore to require a conscious [[mind]]. Consider the following example: [[economic statistics]] represent an [[Economics|economy]], however inaccurately. What are commonly referred to as [[data]] in [[computing]], [[statistics]], and other fields, are forms of information in this sense. The [[electromagnetism|electro-magnetic]] patterns in a [[computer network]] and connected [[device]]s are related to something other than the pattern itself, such as [[text]] to be displayed and [[Computer keyboard|keyboard]] input. [[Signal (information theory)|Signal]]s, [[sign]]s, and [[symbol]]s are also in this category. On the other hand, according to [[semiotics]], data is symbols with certain syntax and information is data with a certain semantic. [[Painting]] and [[drawing]] contain information to the extent that they represent something such as an assortment of objects on a table, a [[profile]], or a [[landscape]]. In other words, when a pattern of something is transposed to a pattern of something else, the latter is information. This type of information still assumes some involvement of conscious mind, of either the entity constructing the representation, or the entity interpreting it.
 
   
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==As sensory input ==
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If you accept that information can be defined merely as a pattern, does it not follow that neither [[utility]] nor meaning are necessary components of information? Surely a distinction must be made between raw unprocessed data and information which possesses utility, [[value]] or some quantum of [[meaning]]. Information may indeed be characterised as a pattern; it is a [[necessary]] condition, but not [[sufficient]]. For example a telephone book follows a specific pattern: name, address , telephone number.
 
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Often information is viewed as a type of [[input]] to an [[organism]] or designed device. Inputs are of two kinds. Some inputs are important to the function of the organism (for example, food) or device ([[energy]]) by themselves. In his book ''Sensory Ecology,'' Dusenbery<!-- who? --> called these causal inputs. Other inputs (information) are important only because they are associated with causal inputs and can be used to predict the occurrence of a causal input at a later time (and perhaps another place). Some information is important because of association with other information but eventually there must be a connection to a causal input. In practice, information is usually carried by weak stimuli that must be detected by specialized sensory systems and amplified by energy inputs before they can be functional to the organism or device. For example, light is often a causal input to plants but provides information to animals. The colored light reflected from a flower is too weak to do much photosynthetic work but the visual system of the bee detects it and the bee's nervous system uses the information to guide the bee to the flower, where the bee often finds nectar or pollen, which are causal inputs, serving a nutritional function.
   
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Information is any type of sensory input. When an organism with a [[nervous system]] receives an input, it transforms the input into an electrical signal. This is regarded information by some. The idea of representation is still relevant, but in a slightly different manner. That is, while [[abstract painting]] does not represent anything concretely, when the viewer sees the painting, it is nevertheless transformed into electrical signals that create a representation of the painting. Defined this way, information does not have to be related to truth, communication, or representation of an object. [[Entertainment]] in general is not intended to be informative. [[Music]], the [[performing arts]], [[amusement park]]s, works of [[fiction]] and so on are thus forms of information in this sense, but they are not necessarily forms of information according to some definitions given above. Consider another example: food supplies both nutrition and taste for those who eat it. If information is equated to sensory input, then nutrition is not information but taste is.
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An individual entry does not become "informative" in some sense unless and until it possesses some degree of utility, value or meaning. For example, someone might look up a girlfriend's number, might order a take away etc. The vast majority of numbers will never be construed as "information" in any meaningful sense. The gap between data and information is only closed by a behavioural bridge whereby some value, utility or meaning is added to transform mere data or pattern into information.
  
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When one constructs a representation of an object, one can selectively extract from the object ([[sampling]]) or use a [[system]] of signs to replace ([[encode|encoding]]), or both. The sampling and encoding result in representation. An example of the former is a "sample" of a product; an example of the latter is "verbal description" of a product. Both contain information of the product, however inaccurate. When one interprets representation, one can predict a broader pattern from a limited number of observations (inference) or understand the relation between patterns of two different things ([[decode|decoding]]). One example of the former is to sip a [[soup]] to know if it is spoiled; an example of the latter is examining footprints to determine the animal and its condition. In both cases, information sources are not constructed or presented by some "sender" of information. To repeat, information in this sense does not assume direct communication, but it assumes involvement of some conscious mind.
  
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Regardless, information is dependent upon, but usually unrelated to and separate from, the medium or media used to express it. In other words, the position of a theoretical series of bits, or even the output once interpreted by a computer or similar device, is unimportant, except when someone or something is present to interpret the information. Therefore, a quantity of information is totally distinct from its medium.
  
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== Information as sensory input ==
  
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Often information is viewed as a type of [[input]] to an [[organism]] or designed [[device]]. Inputs are of two kinds. Some inputs are important to the function of the organism (for example, food) or device ([[energy]]) by themselves. In his book ''Sensory Ecology,'' Dusenbery<!-- who? --> called these causal inputs. Other inputs (information) are important only because they are associated with causal inputs and can be used to predict the occurrence of a causal input at a later time (and perhaps another place). Some information is important because of association with other information but eventually there must be a connection to a causal input. In practice, information is usually carried by weak stimuli that must be detected by specialized sensory systems and amplified by energy inputs before they can be functional to the organism or device. For example, light is often a causal input to plants but provides information to animals. The colored light reflected from a flower is too weak to do much photosynthetic work but the visual system of the bee detects it and the bee's nervous system uses the information to guide the bee to the flower, where the bee often finds nectar or pollen, which are causal inputs, serving a nutritional function.
  
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Information is any type of sensory input. When an [[organism]] with a [[nervous system]] receives an input, it transforms the input into an electrical signal. This is regarded information by some. The idea of representation is still relevant, but in a slightly different manner. That is, while [[abstract painting]] does not represent anything concretely, when the viewer sees the painting, it is nevertheless transformed into electrical signals that create a representation of the painting. Defined this way, information does not have to be related to truth, communication, or representation of an object. [[Entertainment]] in general is not intended to be informative. [[Music]], the [[performing arts]], [[amusement park]]s, works of [[fiction]] and so on are thus forms of information in this sense, but they are not forms of information according to the previous definitions above. Consider another example: food supplies both nutrition and taste for those who eat it. If information is equated to sensory input, then nutrition is not information but taste is.
  
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== Information as an influence which leads to a transformation ==
  
   
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==As an influence which leads to a transformation ==
 
Information is any type of pattern that influences the formation or transformation of other patterns. In this sense, there is no need for a conscious mind to perceive, much less appreciate, the pattern. Consider, for example, [[DNA]]. The sequence of [[nucleotide]]s is a pattern that influences the formation and development of an organism without any need for a conscious mind. [[Systems theory]] at times seems to refer to information in this sense, assuming information does not necessarily involve any conscious mind, and patterns circulating (due to [[feedback]]) in the system can be called information. In other words, it can be said that information in this sense is something potentially perceived as representation, though not created or presented for that purpose.
  
Information is any type of pattern that influences the formation or transformation of other patterns. In this sense, there is no need for a conscious mind to perceive, much less appreciate, the pattern. Consider, for example, [[DNA]]. The sequence of [[nucleotide]]s is a pattern that influences the formation and development of an organism without any need for a conscious mind. [[Systems theory]] at times seems to refer to information in this sense, assuming information does not necessarily involve any conscious mind, and patterns circulating (due to [[feedback]]) in the system can be called information. In other words, it can be said that information in this sense is something potentially perceived as representation, though not created or presented for that purpose.
   
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If, however, the premise of "influence" implies that information has been perceived by a conscious mind and also interpreted by it, the specific context associated with this interpretation may cause the transformation of the information into [[knowledge]]. Complex definitions of both "information" and "knowledge" make such semantic and logical analysis difficult, but the condition of "transformation" is an important point in the study of information as it relates to knowledge, especially in the business discipline of [[knowledge management]]. In this practice, tools and processes are used to assist a [[knowledge worker]] in performing research and making decisions, including steps such as:
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When [[Marshall McLuhan]] speaks of [[Medium|media]] and their effects on human cultures, he refers to the structure of artifacts that in turn shape our behaviors and mindsets. Also, [[pheromone]]s are often said to be "information" in this sense.
  
   
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* reviewing information in order to effectively derive value and meaning
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In 2003, J. D. Bekenstein claimed there is a growing trend in [[physics]] to define the physical world as being made of information itself (and thus information is defined in this way).
 
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* referencing [[metadata]] if any is available
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* establishing a relevant [[context]], often selecting from many possible contexts
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* deriving new [[knowledge]] from the information
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* making decisions or [[recommendation]]s from the resulting knowledge.
   
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Stewart (2001) argues that the transformation of information into knowledge is a critical one, lying at the core of value creation and [[competitive advantage]] for the modern enterprise.
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See the section below on information as a property in physics. (Also see [[Gregory Bateson]].)
  
   
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When [[Marshall McLuhan]] speaks of [[media (communication)|media]] and their effects on human cultures, he refers to the structure of [[cultural artifact|artifacts]] that in turn shape our behaviors and mindsets. Also, [[pheromone]]s are often said to be "information" in this sense.
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== Information as a property in physics ==
  
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''Main article: [[Physical information]]''
  
   
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== As records ==
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Information has a well defined meaning in [[physics]]. Examples of this include the phenomenon of [[quantum entanglement]] where particles can interact without reference to their separation or the speed of light. Information itself cannot travel faster than light even if the information is transmitted indirectly. This could lead to the fact that all attempts at physically observing a particle with an "entangled" relationship to another are slowed down, even though the particles are not connected in any other way other than by the information they carry.
  
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Records are a specialized form of information. Essentially, records are information produced consciously or as by-products of business activities or transactions and retained because of their value. Primarily their value is as evidence of the activities of the organization but they may also be retained for their informational value. Sound [[records management]] ensures that the integrity of records is preserved for as long as they are required.
   
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The international standard on records management, ISO 15489, defines records as "information created, received, and maintained as evidence and information by an organization or person, in pursuance of legal obligations or in the transaction of business". The International Committee on Archives (ICA) Committee on electronic records defined a record as, "a specific piece of recorded information generated, collected or received in the initiation, conduct or completion of an activity and that comprises sufficient content, context and structure to provide proof or evidence of that activity".
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Another link is demonstrated by the [[Maxwell's demon]] thought experiment. In this experiment, a direct relationship between information and another physical property, [[entropy]], is demonstrated. A consequence is that it is impossible to destroy information without increasing the entropy of a system; in practical terms this often means generating heat. Thus, in the study of [[logic gates]], the theoretical lower bound of thermal energy released by an ''AND gate'' is more than for the ''NOT gate'' (because information is destroyed in an ''AND gate'' and simply converted in an ''NOT gate''). Physical information is of particular importance in the theory of [[quantum computers]].
  
   
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Records may be maintained to retain [[corporate memory]] of the organization or to meet legal, fiscal or accountability requirements imposed on the organization. Willis (2005) expressed the view that sound management of business records and information delivered "…six key requirements for good [[corporate governance]]…transparency; accountability; due process; compliance; meeting statutory and common law requirements; and security of personal and corporate information."
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== Etymology ==
  
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According to the [[Oxford English Dictionary]], the earliest historical meaning of the word ''information'' in [[English language|English]] was the act of ''informing'', or giving form or shape to the mind, as in education, instruction, or training. A quote from 1387: "Five books come down from heaven for information of mankind." It was also used for an ''item'' of training, ''e.g.'' a particular instruction. "Melibee had heard the great skills and reasons of Dame Prudence, and her wise informations and techniques." (1386)
  
   
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== Information and semiotics ==
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The English word was apparently derived by adding the common "noun of action" ending "''-ation''" (descended through French from Latin "''-tio''") to the earlier verb ''to inform'', in the sense of to give form to the mind, to discipline, instruct, teach: "Men so wise should go and inform their kings." (1330) ''Inform'' itself comes (via French) from the Latin verb ''informare'', to give form to, to form an idea of. Furthermore, Latin itself already even contained the word ''informatio'' meaning concept or idea, but the extent to which this may have influenced the development of the word ''information'' in English is unclear.
  
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Beynon-Davies <ref>Beynon-Davies P. (2002). Information Systems: an introduction to informatics in Organisations. Palgrave, Basingstoke, UK. ISBN 0-333-96390-3</ref> explains the multi-faceted concept of information in terms of signs and signal-sign systems. Signs themselves can be considered in terms of four inter-dependent levels, layers or branches of [[semiotics]]: pragmatics, semantics, syntax, and empirics. These four layers serve to connect the social world on the one hand with the physical or technical world on the other.
   
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[[Pragmatics]] is concerned with the purpose of communication. Pragmatics links the issue of signs with that of intention. The focus of pragmatics is on the intentions of human agents underlying communicative behaviour. In other words, intentions link language to action.
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As a final note, the ancient Greek word for ''form'' was eidos, and this word was famously used in a technical philosophical sense by [[Plato]] (and later Aristotle) to denote the ideal identity or essence of something (see [[The Forms]]).
  
   
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[[Semantics]] is concerned with the meaning of a message conveyed in a communicative act. Semantics considers the content of communication. Semantics is the study of the meaning of signs - the association between signs and behaviour. Semantics can be considered as the study of the link between symbols and their referents or concepts; particularly the way in which signs relate to human behaviour.
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== Information is not data ==
  
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The words, ''information'' and ''[[data]]'', are used interchangeably in many contexts. This may lead to their confusion. However, they are not synonyms.
 
   
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[[Syntax]] is concerned with the formalism used to represent a message. Syntax as an area studies the form of communication in terms of the logic and grammar of sign systems. Syntax is devoted to the study of the form rather than the content of signs and sign-systems.
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Often data is defined as raw facts while information is processed data (as is the case in most of the article below). Another distinction that is made is that information is the things that we know and data is the representation of the information. As an example, we may be thinking about a favorite niece's age, who is four. We would tend to represent that with Arabic numerals (4), but we could represent it using Roman numerals (IV), tick marks (||||), or any other way we agree on. The information has not changed in each case, although the data has. Note that we tend to think of information in terms of declarative [[knowledge]]. That is, the facts we know such as a temperature, an age, etc. Information can also be skills and things we know how to do, which is called procedural knowledge.
  
   
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Empirics is the study of the signals used to carry a message; the physical characteristics of the medium of communication. Empirics is devoted to the study of communication channels and their characteristics, e.g., sound, light, electronic transmission etc.
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An important consequence of this distinction is that information has [[meaning]] (i.e.: can inform), while data does not. Computers work with data (representations) and not information (meanings). This is why a computer will calculate the average employee number even though it is meaningless.
  
   
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Nielsen (2008) discusses the relationship between semiotics and information in relation to dictionaries. The concept of [[lexicographic information cost]]s is introduced and refers to the efforts users of dictionaries need to make in order to, first, find the data sought and, secondly, understand the data so that they can generate information.
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Note that one person's information may be another's data depending on whether the recipient understand the data (or its context). Also, when someone (or some<em>thing</em>, such as a [[computer system]]) is given a fact, it may only be data, but when they make sense of (or interpret) it, often by bringing it together with other facts, it may become information.
  
   
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Communication normally exists within the context of some social situation. The social situation sets the context for the intentions conveyed (pragmatics) and the form in which communication takes place. In a communicative situation intentions are expressed through messages which comprise collections of inter-related signs taken from a language which is mutually understood by the agents involved in the communication. Mutual understanding implies that agents involved understand the chosen language in terms of its agreed syntax (syntactics) and semantics. The sender codes the message in the language and sends the message as signals along some communication channel (empirics). The chosen communication channel will have inherent properties which determine outcomes such as the speed with which communication can take place and over what distance.
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Information is usually thought of as, in a strict sense, a subset of data. However, sometimes the reverse interpretation can be taken (such as describing data as "raw information"). Data may also have a more specific sense in some fields (e.g.: referring to a certain type or set of <em>information</em> used in that context). When used pragmatically in everyday speech, it usually specifically refers to collections of numbers, or, in a wider sense, to any content not of relevance or interest to the speaker, or not (yet) understood by the speaker themselves in particular.
  
   
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More recently Shu-Kun Lin proposed a simple definition of information: Information is the amount of the data after data compression.
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Data is unstructured, lacks context and may not be relevant to the recipient. When data is correctly organized, filtered and presented with context it can become information because it then has "value" to the recipient.<!-- rm? -->
  
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Data which is not information (i.e.: has not yet informed or been given a context) is often called '''raw data'''.
  
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<!-- add link to content and explain difference to? -->
  
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== References ==
  
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* Bekenstein, Jacob D. (2003, August). Information in the [[holographic principle|holographic universe]]. ''Scientific American''. Retrieved from http://www.referencenter.com
  
   
 
== See also ==
  
== See also ==
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* [[Gregory Bateson]]
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* [[Medium]]
  
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* [[Knowledge level]]
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* [[Lexicographic information cost]]
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* [[Meta-information in linguistics]]
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* [[Philosophy of information]]
 
* [[Prediction]]
  
* [[Prediction]]
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* [[Propaganda model]]
  
* [[Propaganda model]]
 
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* [[Receiver operating characteristic]]
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* [[Relevance]]
 
* [[Satisficing]]
  
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**[[Claude Shannon]]
  
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== External links ==
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== Notes ==
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{{reflist}}
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* [http://isria.com International Security Research & Intelligence Agency], a consulting company specialized in information and international security-related issues that provides internet users with an [http://osint.isria.com Open Sources Center].
  
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* [http://plato.stanford.edu/entries/information-semantic/ Semantic Conceptions of Information] Review by Luciano Floridi for the [[Stanford Encyclopedia of Philosophy]]
  
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== Further reading ==
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* Alan Liu (2004). ''The Laws of Cool: Knowledge Work and the Culture of Information'', [[University of Chicago Press]]
  ⚫
* Bekenstein, Jacob D. (2003, August). Information in the [[holographic principle|holographic universe]]. ''Scientific American''.
  +
* Shu-Kun Lin (2008). 'Gibbs Paradox and the Concepts of Information, Symmetry, Similarity and Their Relationship', ''Entropy'', 10 (1), 1-5. Available online at [http://www.mdpi.com/1099-4300/10/1/1 Entropy journal website].
  +
* [[Luciano Floridi]], (2005). 'Is Information Meaningful Data?', ''Philosophy and Phenomenological Research'', 70 (2), pp.&nbsp;351 – 370. Available online at [http://www.wolfson.ox.ac.uk/~floridi/pdf/iimd.pdf Oxford University]
  +
* [[Luciano Floridi]], (2005). 'Semantic Conceptions of Information', ''The Stanford Encyclopedia of Philosophy'' (Winter 2005 Edition), Edward N. Zalta (ed.). Available online at [http://plato.stanford.edu/entries/information-semantic/ Stanford University]
  +
* Sandro Nielsen: 'The Effect of Lexicographical Information Costs on Dictionary Making and Use', ''Lexikos'' 18/2008, 170-189.
  +
* Stewart, Thomas, (2001). Wealth of Knowledge. Doubleday, New York, NY, 379 p.
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* Young, Paul. The Nature of Information (1987). Greenwood Publishing Group, Westport, Ct. ISBN 0-275-92698-2.
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==External links==
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{{wiktionary}}
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{{wikiquote}}
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*[http://plato.stanford.edu/entries/information-semantic/ Semantic Conceptions of Information] Review by [[Luciano Floridi]] for the [[Stanford Encyclopedia of Philosophy]]
 
* [http://pespmc1.vub.ac.be/ASC/NEGENTROPY.html Principia Cybernetica entry on negentropy]
  
* [http://pespmc1.vub.ac.be/ASC/NEGENTROPY.html Principia Cybernetica entry on negentropy]
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* [http://www.optics.arizona.edu/Frieden/Fisher_Information.htm Fisher Information, a New Paradigm for Science: Introduction, Uncertainty principles, Wave equations, Ideas of Escher, Kant, Plato and Wheeler.] This essay is continually revised in the light of ongoing research.
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* [http://www.princeton.edu/~pear/IU.pdf Information & Uncertainty in Remote Perception Research]
  
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* [http://www2.sims.berkeley.edu/research/projects/how-much-info-2003/index.htm How Much Information? 2003] an attempt to estimate how much new information is created each year (study was produced by faculty and students at the [[UC Berkeley School of Information|School of Information Management and Systems]] at the [[University of California at Berkeley]].)
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* [http://www.princeton.edu/~pear/JahnATpages.pdf Information, Consciousness & Health]
  
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Latest revision as of 09:38, 24 December 2011

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Information as a concept has many meanings, from everyday usage to technical settings. The concept of information is closely related to notions of constraint, communication, control, data, form, instruction, knowledge, meaning, mental stimulus, pattern, perception, and representation. In its most restricted technical meaning, information is an ordered sequence of symbols.

The English word was apparently derived from the Latin accusative form (informationem) of the nominative (informatio): this noun is in its turn derived from the verb "informare" (to inform) in the sense of "to give form to the mind", "to discipline", "instruct", "teach": "Men so wise should go and inform their kings." (1330) Inform itself comes (via French) from the Latin verb informare, to give form to, to form an idea of. Furthermore, Latin itself already contained the word informatio meaning concept or idea, but the extent to which this may have influenced the development of the word information in English is unclear.

As a final note, the ancient Greek word for form was "μορφή" (morf -> morphe, Morph) and also είδος eidos (kind, idea, shape, set), the latter word was famously used in a technical philosophical sense by Plato (and later Aristotle) to denote the ideal identity or essence of something (see Theory of forms). "Eidos" can also be associated with thought, proposition or even concept.

As a message

Information is a term with many meanings depending on context, but is as a rule closely related to such concepts as meaning, knowledge, instruction, communication, representation, and mental stimulus. Simply stated, information is a message received and understood. In terms of data, it can be defined as a collection of facts from which conclusions may be drawn. There are many other aspects of information since it is the knowledge acquired through study or experience or instruction. But overall, information is the result of processing, manipulating and organizing data in a way that adds to the knowledge of the person receiving it.

Information is the state of a system of interest. Message is the information materialized.

Information is a quality of a message from a sender to one or more receivers. Information is always about something (size of a parameter, occurrence of an event, value, ethics, etc). Viewed in this manner, information does not have to be accurate; it may be a truth or a lie, or just the sound of a falling tree. Even a disruptive noise used to inhibit the flow of communication and create misunderstanding would in this view be a form of information. However, generally speaking, if the amount of information in the received message increases, the message is more accurate.

This model assumes there is a definite sender and at least one receiver. Many refinements of the model assume the existence of a common language understood by the sender and at least one of the receivers. An important variation identifies information as that which would be communicated by a message if it were sent from a sender to a receiver capable of understanding the message. In another variation, it is not required that the sender be capable of understanding the message, or even cognizant that there is a message, making information something that can be extracted from an environment, e.g., through observation, reading or measurement.

Communication theory provides a numerical measure of the uncertainty of an outcome. For example, we can say that "the signal contained thousands of bits of information". Communication theory tends to use the concept of information entropy, generally attributed to Claude Shannon, see below.

Another form of information is Fisher information, a concept of R.A. Fisher. This is used in application of statistics to estimation theory and to science in general. Fisher information is thought of as the amount of information that a message carries about an unobservable parameter. It can be computed from knowledge of the likelihood function defining the system. For example, with a normal likelihood function, the Fisher information is the reciprocal of the variance of the law. In the absence of knowledge of the likelihood law, the Fisher information may be computed from normally distributed score data as the reciprocal of their second moment.

Even though information and data are often used interchangeably, they are actually very different. Data is a set of unrelated information, and as such is of no use until it is properly evaluated. Upon evaluation, once there is some significant relation between data, and they show some relevance, then they are converted into information. Now this same data can be used for different purposes. Thus, till the data convey some information, they are not useful and therefore not information.

Measuring information entropy

The view of information as a message came into prominence with the publication in 1948 of an influential paper by Claude Shannon, "A Mathematical Theory of Communication." This thesis provides the foundations of information theory and endows the word information not only with a technical meaning but also a measure. If the sending device is equally likely to send any one of a set of N messages, then the preferred measure of "the information produced when one message is chosen from the set" is the base two logarithm of (This measure is called self-information). In this paper, Shannon continues:

The choice of a logarithmic base corresponds to the choice of a unit for measuring information. If the base 2 is used the resulting units may be called binary digits, or more briefly bits, a word suggested by J. W. Tukey. A device with two stable positions, such as a relay or a flip-flop circuit, can store one bit of information. N such devices can store N bits…[1]


A complementary way of measuring information is provided by algorithmic information theory. In brief, this measures the information content of a list of symbols based on how predictable they are, or more specifically how easy it is to compute the list through a program: the information content of a sequence is the number of bits of the shortest program that computes it. The sequence below would have a very low algorithmic information measurement since it is a very predictable pattern, and as the pattern continues the measurement would not change. Shannon information would give the same information measurement for each symbol, since they are statistically random, and each new symbol would increase the measurement.

123456789101112131415161718192021

It is important to recognize the limitations of traditional information theory and algorithmic information theory from the perspective of human meaning. For example, when referring to the meaning content of a message Shannon noted “Frequently the messages have meaning… these semantic aspects of communication are irrelevant to the engineering problem. The significant aspect is that the actual message is one selected from a set of possible messages” (emphasis in original).

In information theory signals are part of a process, not a substance; they do something, they do not contain any specific meaning. Combining algorithmic information theory and information theory we can conclude that the most random signal contains the most information as it can be interpreted in any way and cannot be compressed.[citation needed]

Michael Reddy noted that "'signals' of the mathematical theory are 'patterns that can be exchanged'. There is no message contained in the signal, the signals convey the ability to select from a set of possible messages." In information theory "the system must be designed to operate for each possible selection, not just the one which will actually be chosen since this is unknown at the time of design".

As sensory input

Often information is viewed as a type of input to an organism or designed device. Inputs are of two kinds. Some inputs are important to the function of the organism (for example, food) or device (energy) by themselves. In his book Sensory Ecology, Dusenbery called these causal inputs. Other inputs (information) are important only because they are associated with causal inputs and can be used to predict the occurrence of a causal input at a later time (and perhaps another place). Some information is important because of association with other information but eventually there must be a connection to a causal input. In practice, information is usually carried by weak stimuli that must be detected by specialized sensory systems and amplified by energy inputs before they can be functional to the organism or device. For example, light is often a causal input to plants but provides information to animals. The colored light reflected from a flower is too weak to do much photosynthetic work but the visual system of the bee detects it and the bee's nervous system uses the information to guide the bee to the flower, where the bee often finds nectar or pollen, which are causal inputs, serving a nutritional function.

Information is any type of sensory input. When an organism with a nervous system receives an input, it transforms the input into an electrical signal. This is regarded information by some. The idea of representation is still relevant, but in a slightly different manner. That is, while abstract painting does not represent anything concretely, when the viewer sees the painting, it is nevertheless transformed into electrical signals that create a representation of the painting. Defined this way, information does not have to be related to truth, communication, or representation of an object. Entertainment in general is not intended to be informative. Music, the performing arts, amusement parks, works of fiction and so on are thus forms of information in this sense, but they are not necessarily forms of information according to some definitions given above. Consider another example: food supplies both nutrition and taste for those who eat it. If information is equated to sensory input, then nutrition is not information but taste is.

As an influence which leads to a transformation

Information is any type of pattern that influences the formation or transformation of other patterns. In this sense, there is no need for a conscious mind to perceive, much less appreciate, the pattern. Consider, for example, DNA. The sequence of nucleotides is a pattern that influences the formation and development of an organism without any need for a conscious mind. Systems theory at times seems to refer to information in this sense, assuming information does not necessarily involve any conscious mind, and patterns circulating (due to feedback) in the system can be called information. In other words, it can be said that information in this sense is something potentially perceived as representation, though not created or presented for that purpose.

If, however, the premise of "influence" implies that information has been perceived by a conscious mind and also interpreted by it, the specific context associated with this interpretation may cause the transformation of the information into knowledge. Complex definitions of both "information" and "knowledge" make such semantic and logical analysis difficult, but the condition of "transformation" is an important point in the study of information as it relates to knowledge, especially in the business discipline of knowledge management. In this practice, tools and processes are used to assist a knowledge worker in performing research and making decisions, including steps such as:

  • reviewing information in order to effectively derive value and meaning
  • referencing metadata if any is available
  • establishing a relevant context, often selecting from many possible contexts
  • deriving new knowledge from the information
  • making decisions or recommendations from the resulting knowledge.

Stewart (2001) argues that the transformation of information into knowledge is a critical one, lying at the core of value creation and competitive advantage for the modern enterprise.

When Marshall McLuhan speaks of media and their effects on human cultures, he refers to the structure of artifacts that in turn shape our behaviors and mindsets. Also, pheromones are often said to be "information" in this sense.

As records

Records are a specialized form of information. Essentially, records are information produced consciously or as by-products of business activities or transactions and retained because of their value. Primarily their value is as evidence of the activities of the organization but they may also be retained for their informational value. Sound records management ensures that the integrity of records is preserved for as long as they are required.

The international standard on records management, ISO 15489, defines records as "information created, received, and maintained as evidence and information by an organization or person, in pursuance of legal obligations or in the transaction of business". The International Committee on Archives (ICA) Committee on electronic records defined a record as, "a specific piece of recorded information generated, collected or received in the initiation, conduct or completion of an activity and that comprises sufficient content, context and structure to provide proof or evidence of that activity".

Records may be maintained to retain corporate memory of the organization or to meet legal, fiscal or accountability requirements imposed on the organization. Willis (2005) expressed the view that sound management of business records and information delivered "…six key requirements for good corporate governance…transparency; accountability; due process; compliance; meeting statutory and common law requirements; and security of personal and corporate information."

Information and semiotics

Beynon-Davies [2] explains the multi-faceted concept of information in terms of signs and signal-sign systems. Signs themselves can be considered in terms of four inter-dependent levels, layers or branches of semiotics: pragmatics, semantics, syntax, and empirics. These four layers serve to connect the social world on the one hand with the physical or technical world on the other.

Pragmatics is concerned with the purpose of communication. Pragmatics links the issue of signs with that of intention. The focus of pragmatics is on the intentions of human agents underlying communicative behaviour. In other words, intentions link language to action.

Semantics is concerned with the meaning of a message conveyed in a communicative act. Semantics considers the content of communication. Semantics is the study of the meaning of signs - the association between signs and behaviour. Semantics can be considered as the study of the link between symbols and their referents or concepts; particularly the way in which signs relate to human behaviour.

Syntax is concerned with the formalism used to represent a message. Syntax as an area studies the form of communication in terms of the logic and grammar of sign systems. Syntax is devoted to the study of the form rather than the content of signs and sign-systems.

Empirics is the study of the signals used to carry a message; the physical characteristics of the medium of communication. Empirics is devoted to the study of communication channels and their characteristics, e.g., sound, light, electronic transmission etc.

Nielsen (2008) discusses the relationship between semiotics and information in relation to dictionaries. The concept of lexicographic information costs is introduced and refers to the efforts users of dictionaries need to make in order to, first, find the data sought and, secondly, understand the data so that they can generate information.

Communication normally exists within the context of some social situation. The social situation sets the context for the intentions conveyed (pragmatics) and the form in which communication takes place. In a communicative situation intentions are expressed through messages which comprise collections of inter-related signs taken from a language which is mutually understood by the agents involved in the communication. Mutual understanding implies that agents involved understand the chosen language in terms of its agreed syntax (syntactics) and semantics. The sender codes the message in the language and sends the message as signals along some communication channel (empirics). The chosen communication channel will have inherent properties which determine outcomes such as the speed with which communication can take place and over what distance.

More recently Shu-Kun Lin proposed a simple definition of information: Information is the amount of the data after data compression.

See also

Notes

  1. ↑ The Bell System Technical Journal, Vol. 27, p. 379, (July 1948).
  2. ↑ Beynon-Davies P. (2002). Information Systems: an introduction to informatics in Organisations. Palgrave, Basingstoke, UK. ISBN 0-333-96390-3

Further reading

  • Alan Liu (2004). The Laws of Cool: Knowledge Work and the Culture of Information, University of Chicago Press
  • Bekenstein, Jacob D. (2003, August). Information in the holographic universe. Scientific American.
  • Shu-Kun Lin (2008). 'Gibbs Paradox and the Concepts of Information, Symmetry, Similarity and Their Relationship', Entropy, 10 (1), 1-5. Available online at Entropy journal website.
  • Luciano Floridi, (2005). 'Is Information Meaningful Data?', Philosophy and Phenomenological Research, 70 (2), pp. 351 – 370. Available online at Oxford University
  • Luciano Floridi, (2005). 'Semantic Conceptions of Information', The Stanford Encyclopedia of Philosophy (Winter 2005 Edition), Edward N. Zalta (ed.). Available online at Stanford University
  • Sandro Nielsen: 'The Effect of Lexicographical Information Costs on Dictionary Making and Use', Lexikos 18/2008, 170-189.
  • Stewart, Thomas, (2001). Wealth of Knowledge. Doubleday, New York, NY, 379 p.
  • Young, Paul. The Nature of Information (1987). Greenwood Publishing Group, Westport, Ct. ISBN 0-275-92698-2.

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