Information

Information can be thought of as the resolution of uncertainty; it is that which answers the question of "What an entity is" and thus defines both its essence and nature of its characteristics. The concept of information has different meanings in different contexts.[1] Thus the concept becomes related to notions of constraint, communication, control, data, form, education, knowledge, meaning, understanding, mental stimuli, pattern, perception, representation, and entropy.

For the Danish newspaper, see Dagbladet Information. For the formal criminal charge, see Information (formal criminal charge).
For other uses, see Information (disambiguation).

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Information is associated with data, as data represent values attributed to parameters, and information is data in context and with meaning attached. Information also relates to knowledge, as knowledge signifies understanding of an abstract or concrete concept.[2]

In terms of communication, information is expressed either as the content of a message or through direct or indirect observation. That which is perceived can be construed as a message in its own right, and in that sense, information is always conveyed as the content of a message.

Information can be encoded into various forms for transmission and interpretation (for example, information may be encoded into a sequence of signs, or transmitted via a signal). It can also be encrypted for safe storage and communication.

The uncertainty of an event is measured by its probability of occurrence and is inversely proportional to that. The more uncertain an event, the more information is required to resolve uncertainty of that event. The bit is a typical unit of information, but other units such as the nat may be used. For example, the information encoded in one "fair" coin flip is log2(2/1) = 1 bit, and in two fair coin flips is log2(4/1) = 2 bits.

Etymology
See also: History of the word and concept "information"

The English word "Information" apparently derives from the Latin stem (information-) of the nominative (informatio): this noun derives from the verb informare (to inform) in the sense of "to give form to the mind", "to discipline", "instruct", "teach". Inform itself comes (via French informer) from the Latin verb informare, which means to give form, or 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 not clear.

The ancient Greek word for form was μορφή (morphe; cf. morph) and also εἶδος (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.

The ancient Greek word for information is πληροφορία, which transliterates (plērophoria) from πλήρης (plērēs) "fully" and φέρω (phorein) frequentative of (pherein) to carry through. It literally means "bears fully" or "conveys fully". In modern Greek the word Πληροφορία is still in daily use and has the same meaning as the word information in English. In addition to its primary meaning, the word Πληροφορία as a symbol has deep roots in Aristotle's semiotic triangle. In this regard it can be interpreted to communicate information to the one decoding that specific type of sign. This is something that occurs frequently with the etymology of many words in ancient and modern Greek where there is a very strong denotative relationship between the signifier, e.g. the word symbol that conveys a specific encoded interpretation, and the signified, e.g. a concept whose meaning the interpreter attempts to decode.

In English, "information" is an uncountable mass noun.

Information theory approach
Main article: Information theory

In information theory, information is taken as an ordered sequence of symbols from an alphabet, say an input alphabet χ, and an output alphabet ϒ. Information processing consists of an input-output function that maps any input sequence from χ into an output sequence from ϒ. The mapping may be probabilistic or deterministic. It may have memory or be memoryless.[3]

As sensory input

Often information can be viewed as a type of input to an organism or system. Inputs are of two kinds; some inputs are important to the function of the organism (for example, food) or system (energy) by themselves. In his book Sensory Ecology[4] biophysicist David B. 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 system. For example, light is mainly (but not only, e.g. plants can grow in the direction of the lightsource) a causal input to plants but for animals it only provides information. The colored light reflected from a flower is too weak for photosynthesis 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.

As representation and complexity

The cognitive scientist and applied mathematician Ronaldo Vigo argues that information is a concept that requires at least two related entities to make quantitative sense. These are, any dimensionally defined category of objects S, and any of its subsets R. R, in essence, is a representation of S, or, in other words, conveys representational (and hence, conceptual) information about S. Vigo then defines the amount of information that R conveys about S as the rate of change in the complexity of S whenever the objects in R are removed from S. Under "Vigo information", pattern, invariance, complexity, representation, and information—five fundamental constructs of universal science—are unified under a novel mathematical framework.[5][6][7] Among other things, the framework aims to overcome the limitations of Shannon-Weaver information when attempting to characterize and measure subjective information.

As an influence that leads to transformation

Information is any type of pattern that influences the formation or transformation of other patterns.[8][9] 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. One might argue though that for a human to consciously define a pattern, for example a nucleotide, naturally involves conscious information processing.

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. For example, Gregory Bateson defines "information" as a "difference that makes a difference".[10]

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:

  • Review information to effectively derive value and meaning
  • Reference metadata if available
  • Establish relevant context, often from many possible contexts
  • Derive new knowledge from the information
  • Make decisions or recommendations from the resulting knowledge

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

The Danish Dictionary of Information Terms[11] argues that information only provides an answer to a posed question. Whether the answer provides knowledge depends on the informed person. So a generalized definition of the concept should be: "Information" = An answer to a specific question".

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 a property in physics
Main article: Physical information

Information has a well-defined meaning in physics. In 2003 J. D. Bekenstein claimed that a growing trend in physics was to define the physical world as being made up of information itself (and thus information is defined in this way) (see Digital physics). Examples of this include the phenomenon of quantum entanglement, where particles can interact without reference to their separation or the speed of light. Material information itself cannot travel faster than light even if that information is transmitted indirectly. This could lead to all attempts at physically observing a particle with an "entangled" relationship to another being slowed, even though the particles are not connected in any other way other than by the information they carry.

The mathematical universe hypothesis suggests a new paradigm, in which virtually everything, from particles and fields, through biological entities and consciousness, to the multiverse itself, could be described by mathematical patterns of information. By the same token, the cosmic void can be conceived of as the absence of material information in space (setting aside the virtual particles that pop in and out of existence due to quantum fluctuations, as well as the gravitational field and the dark energy). Nothingness can be understood then as that within which no matter, energy, space, time, or any other type of information could exist, which would be possible if symmetry and structure break within the manifold of the multiverse (i.e. the manifold would have tears or holes). Physical information exists beyond event horizons, since astronomical observations show that, due to the expansion of the universe, distant objects continue to pass the cosmological horizon, as seen from a present time, local observer point of view.

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. Another more philosophical outcome is that information could be thought of as interchangeable with energy. Toyabe et al. experimentally showed in nature that information can be converted into work.[12] Thus, in the study of logic gates, the theoretical lower bound of thermal energy released by an AND gate is higher than for the NOT gate (because information is destroyed in an AND gate and simply converted in a NOT gate). Physical information is of particular importance in the theory of quantum computers.

In thermodynamics, information is any kind of event that affects the state of a dynamic system that can interpret the information.

The application of information study

The information cycle (addressed as a whole or in its distinct components) is of great concern to information technology, information systems, as well as information science. These fields deal with those processes and techniques pertaining to information capture (through sensors) and generation (through computation, formulation or composition), processing (including encoding, encryption, compression, packaging), transmission (including all telecommunication methods), presentation (including visualization / display methods), storage (such as magnetic or optical, including holographic methods), etc.

Information visualization (shortened as InfoVis) depends on the computation and digital representation of data, and assists users in pattern recognition and anomaly detection.

  • Partial map of the Internet, with nodes representing IP addresses
  • Galactic (including dark) matter distribution in a cubic section of the Universe
  • Information embedded in an abstract mathematical object with symmetry breaking nucleus
  • Visual representation of a strange attractor, with converted data of its fractal structure

Information security (shortened as InfoSec) is the ongoing process of exercising due diligence to protect information, and information systems, from unauthorized access, use, disclosure, destruction, modification, disruption or distribution, through algorithms and procedures focused on monitoring and detection, as well as incident response and repair.

Information analysis is the process of inspecting, transforming, and modelling information, by converting raw data into actionable knowledge, in support of the decision-making process.

Information quality (shortened as InfoQ) is the potential of a dataset to achieve a specific (scientific or practical) goal using a given empirical analysis method.

Information communication represents the convergence of informatics, telecommunication and audio-visual media & content.

Technologically mediated information
Further information: Information Age

It is estimated that the world's technological capacity to store information grew from 2.6 (optimally compressed) exabytes in 1986 – which is the informational equivalent to less than one 730-MB CD-ROM per person (539 MB per person) – to 295 (optimally compressed) exabytes in 2007.[13] This is the informational equivalent of almost 61 CD-ROM per person in 2007.[14]

The world's combined technological capacity to receive information through one-way broadcast networks was the informational equivalent of 174 newspapers per person per day in 2007.[13]

The world's combined effective capacity to exchange information through two-way telecommunication networks was the informational equivalent of 6 newspapers per person per day in 2007.[14]

As of 2007, an estimated 90% of all new information is digital, mostly stored on hard drives.[15]

As records

Records are specialized forms 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".[16] The International Committee on Archives (ICA) Committee on electronic records defined a record as, "recorded information produced or received in the initiation, conduct or completion of an institutional or individual activity and that comprises content, context and structure sufficient to provide evidence of the activity".[17]

Records may be maintained to retain corporate memory of the organization or to meet legal, fiscal or accountability requirements imposed on the organization. Willis 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."[18]

Semiotics

Michael Buckland has classified "information" in terms of its uses: "information as process", "information as knowledge", and "information as thing".[19]

Beynon-Davies[20][21] 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 the context within which signs are used. The focus of pragmatics is on the intentions of living agents underlying communicative behaviour. In other words, pragmatics 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 that signs relate to human behavior.

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.

Nielsen (2008) discusses the relationship between semiotics and information in relation to dictionaries. He introduces the concept of lexicographic information costs and refers to the effort a user of a dictionary must make to first find, and then understand 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 of communication. In a communicative situation intentions are expressed through messages that comprise collections of inter-related signs taken from a language 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 has inherent properties that determine outcomes such as the speed at which communication can take place, and over what distance.

gollark: I don't think the government particularly needs to have information on your gender. Your sex *maybe*.
gollark: > massive number of people... *how* massive?
gollark: > yeah because they know the nhs is shitDid you just say BAD THINGS about the GLORIOUS NHS?!?!?!?!?!?!?!!?!?!?!??!?! You must want to PRIVATIZE IT!!!!!! Initiating orbital laser strike.
gollark: Except Epicbot is JS.
gollark: Python has `random.choices` or something now.

See also

References
  1. A short overview is found in: Luciano Floridi (2010). Information - A Very Short Introduction. Oxford University Press. ISBN 978-0-19-160954-1. The goal of this volume is to provide an outline of what information is...
  2. "Information - Definition of Information by Merriam-Webster". Merriam-webster.com. Retrieved 1 May 2017.
  3. Stephen B. Wicker, Saejoon Kim (2003). Fundamentals of Codes, Graphs, and Iterative Decoding. Springer. pp. 1 ff. ISBN 978-1-4020-7264-2.
  4. Dusenbery, David B. (1992). Sensory Ecology. New York: W.H. Freeman. ISBN 978-0-7167-2333-2.
  5. Vigo, R. (2011). "Representational information: a new general notion and measure of information" (PDF). Information Sciences. 181 (21): 4847–59. doi:10.1016/j.ins.2011.05.020.
  6. Vigo, R. (2013). "Complexity over Uncertainty in Generalized Representational Information Theory (GRIT): A Structure-Sensitive General Theory of Information". Information. 4 (1): 1–30. doi:10.3390/info4010001.
  7. Vigo, R. (2014). Mathematical Principles of Human Conceptual Behavior: The Structural Nature of Conceptual Representation and Processing. New York and London: Scientific Psychology Series, Routledge. ISBN 978-0415714365.
  8. Shannon, Claude E. (1949). The Mathematical Theory of Communication.
  9. Casagrande, David (1999). "Information as verb: Re-conceptualizing information for cognitive and ecological models" (PDF). Journal of Ecological Anthropology. 3 (1): 4–13. doi:10.5038/2162-4593.3.1.1.
  10. Bateson, Gregory (1972). Form, Substance, and Difference, in Steps to an Ecology of Mind. University of Chicago Press. pp. 448–66.
  11. Simonsen, Bo Krantz. "Informationsordbogen - vis begreb". Informationsordbogen.dk. Retrieved 1 May 2017.
  12. Merali, Zeeya (14 November 2010). "Demonic device converts information to energy : Nature News". Nature. doi:10.1038/news.2010.606. Retrieved 1 May 2017.
  13. Hilbert, Martin; López, Priscila (2011). "The World's Technological Capacity to Store, Communicate, and Compute Information". Science. 332 (6025): 60–65. Bibcode:2011Sci...332...60H. doi:10.1126/science.1200970. PMID 21310967. Free access to the article at martinhilbert.net/WorldInfoCapacity.html
  14. "World_info_capacity_animation". YouTube. 11 June 2011. Retrieved 1 May 2017.
  15. Failure Trends in a Large Disk Drive Population. Eduardo Pinheiro, Wolf-Dietrich Weber and Luiz Andre Barroso
  16. ISO 15489
  17. Committee on Electronic Records (February 1997). "Guide For Managing Electronic Records From An Archival Perspective" (PDF). www.ica.org. International Committee on Archives. p. 22. Retrieved 9 February 2019.
  18. Willis, Anthony (1 August 2005). "Corporate governance and management of information and records". Records Management Journal. 15 (2): 86–97. doi:10.1108/09565690510614238.
  19. Buckland, Michael K. (June 1991). "Information as thing". Journal of the American Society for Information Science. 42 (5): 351–360. doi:10.1002/(SICI)1097-4571(199106)42:5<351::AID-ASI5>3.0.CO;2-3.
  20. Beynon-Davies, P. (2002). Information Systems: an introduction to informatics in Organisations. Basingstoke, UK: Palgrave. ISBN 978-0-333-96390-6.
  21. Beynon-Davies, P. (2009). Business Information Systems. Basingstoke: Palgrave. ISBN 978-0-230-20368-6.

Further reading
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