For example, researchers in the field of information Petrichenko E. It lies in the fact that the concept itself has changed along with the change of various historical epochs, and in order to find such a definition, it is necessary to find common features and patterns of this transformation. There is another opinion regarding the universal definition of information. Important sub-fields of information theory include source coding, algorithmic complexity theory, algorithmic information theory, and information-theoretic security. Some other important measures in information theory are mutual information, channel capacity, error exponents, and relative entropy. For example, identifying the outcome of a fair coin flip (with two equally likely outcomes) provides less information (lower entropy) than specifying the outcome from a roll of a die (with six equally likely outcomes).
Entropy quantifies the amount of uncertainty involved in the value of a random variable or the outcome of a random process. The field is at the intersection of probability theory, statistics, computer science, statistical mechanics, information engineering, and electrical engineering.Ī key measure in information theory is entropy. The field was fundamentally established by the works of Harry Nyquist and Ralph Hartley in the 1920s, and Claude Shannon in the 1940s. Information theory is the scientific study of the quantification, storage, and communication of information. A 2011 Science article estimated that 97% of technologically stored information was already in digital bits in 2007, and that the year 2002 was the beginning of the digital age for information storage (with digital storage capacity bypassing analog for the first time). For example, the information encoded in one "fair" coin flip is log 2(2/1) = 1 bit, and in two fair coin flips is log 2(4/1) = 2 bits. It is 'that which reduces uncertainty by half'.
The bit is a typical unit of information. Information theory takes advantage of this by concluding that more uncertain events require more information to resolve their uncertainty. Uncertainty is inversely proportional to the probability of occurrence. The uncertainty of an event is measured by its probability of occurrence. It can also be encrypted for safe storage and communication. 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). 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 is expressed either as the content of a message or through direct or indirect observation. Information can be transmitted in time, via data storage, and space, via communication and telecommunication. Data can represent redundant symbols, but approaches information through optimal data compression. The difference is that information resolves uncertainty. Thus the concept becomes synonymous to notions of constraint, communication, control, data, form, education, knowledge, meaning, understanding, mental stimuli, pattern, perception, proposition, representation, and entropy. The concept of information has different meanings in different contexts. More technically, information can be thought of as the resolution of uncertainty that manifests itself as patterns it answers the question of "What an entity is" and thus defines both its essence and the nature of its characteristics. It provides context for data and enables decision making processes.įor example, a single customer’s sale at a restaurant is data – this becomes information when the business is able to identify the most popular or least popular dish. Information is processed, organized and structured data.
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