In information theory, the term information is used in a special sense; it is a measure of the freedom of choice with which a message is selected from the set of all possible messages. Information is thus distinct from meaning, since it is entirely possible for a string of nonsense words and a meaningful sentence to be equivalent with respect to information content.
Numerically, information is measured in bits (short for binary digit; see binary system). One bit is equivalent to the choice between two equally likely choices. For example, if we know that a coin is to be tossed but are unable to see it as it falls, a message telling whether the coin came up heads or tails gives us one bit of information. When there are several equally likely choices, the number of bits is equal to the logarithm of the number of choices taken to the base two. For example, if a message specifies one of sixteen equally likely choices, it is said to contain four bits of information. When the various choices are not equally probable, the situation is more complex.
Interestingly, the mathematical expression for information content closely resembles the expression for entropy in thermodynamics. The greater the information in a message, the lower its randomness, or "noisiness," and hence the smaller its entropy. Since the information content is, in general, associated with a source that generates messages, it is often called the entropy of the source. Often, because of constraints such as grammar, a source does not use its full range of choice. A source that uses just 70% of its freedom of choice would be said to have a relative entropy of 0.7. The redundancy of such a source is defined as 100% minus the relative entropy, or, in this case, 30%. The redundancy of English is estimated to be about 50%; i.e., about half of the elements used in writing or speaking are freely chosen, and the rest are required by the structure of the language.
A message proceeds along a channel from the source to the receiver; information theory defines for any given channel a limiting capacity or rate at which it can carry information, expressed in bits per second. In general, it is necessary to process, or encode, information from a source before transmitting it through a given channel. For example, a human voice must be encoded before it can be transmitted by telephone. An important theorem of information theory states that if a source with a given entropy feeds information to a channel with a given capacity, and if the source entropy is less than the channel capacity, a code exists for which the frequency of errors may be reduced as low as desired. If the channel capacity is less than the source entropy, no such code exists.
The theory further shows that noise, or random disturbance of the channel, creates uncertainty as to the correspondence between the received signal and the transmitted signal. The average uncertainty in the message when the signal is known is called the equivocation. It is shown that the net effect of noise is to reduce the information capacity of the channel. However, redundancy in a message, as distinguished from redundancy in a source, makes it more likely that the message can be reconstructed at the receiver without error. For example, if something is already known as a certainty, then all messages about it give no information and are 100% redundant, and the information is thus immune to any disturbances of the channel. Using various mathematical means, Shannon was able to define channel capacity for continuous signals, such as music and speech.
See C. E. Shannon and W. Weaver, The Mathematical Theory of Communication (1949); M. Mansuripur, Introduction to Information Theory (1987).
See A. Ishikawa, Future Computer and Information Systems (1986).
See W. Carroll, Persuade or Perish (1948).
Field of mathematics that studies the problems of signal transmission, reception, and processing. It stems from Claude E. Shannon's mathematical methods for measuring the degree of order (nonrandomness) in a signal, which drew largely on probability theory and stochastic processes and led to techniques for determining a source's rate of information production, a channel's capacity to handle information, and the average amount of information in a given type of message. Crucial to the design of communications systems, these techniques have important applications in linguistics, psychology, and even literary theory.
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Acquisition, recording, organization, retrieval, display, and dissemination of information. Today the term usually refers to computer-based operations. Information processing consists of locating and capturing information, using software to manipulate it into a desired form, and outputting the data. An Internet search engine is an example of an information-processing tool, as is any sophisticated information-retrieval system. Seealso data processing.
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Discipline that deals with the processes of storing and transferring information. It attempts to bring together concepts and methods from such varied disciplines as library science, computer science and engineering, linguistics, and psychology to develop techniques and devices to aid in the handling of information. In its early stages in the 1960s, information science was concerned primarily with applying the then-new computer technology to the processing and managing of documents. The applied computer technologies and theoretical studies of information science have since permeated many other disciplines. Computer science and engineering still tend to absorb its theory- and technology-oriented subjects, and management science tends to absorb information-systems subjects.
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Computerized system that relates and displays data collected from a geographic entity in the form of a map. The ability of GIS to overlay existing data with new information and display it in colour on a computer screen is used primarily to conduct analyses and make decisions related to geology, ecology, land use, demographics, transportation, and other domains, most of which relate to the human use of the physical environment. Through the process of geocoding, geographic data from a database is converted into images in the form of maps.
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Data-transmission code used to represent both text (letters, numbers, punctuation marks) and noninput device commands (control characters) for electronic exchange and storage. Standard ASCII uses a string of 7 bits (binary digits) for each symbol and can thus represent 27 = 128 characters. Extended ASCII uses an 8-bit encoding system and can thus represent 28 = 256 characters. While ASCII is still found in legacy data, Unicode, with 8-, 16-, and 32-bit versions, has become standard for modern operating systems and browsers. In particular, the 32-bit version now supports all of the characters in every major language.
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