In science, information is a fact, unit of data, sensory input, or collection of knowledge that can be transmitted, processed, or stored. [1] In human chemistry, information can be understood as a component of the driving force. [2] In thermodynamics and human thermodynamics, beginning in about the 1920s, information began to be questionably associated with entropy, although the merits of this relation vary according to derivation and use.

Sensory perception
In the perspective defined by Scottish physicist James Maxwell, at the age of sixteen, in which, according to definition, the only thing that can be directly perceived by the senses is force, information can also be defined as a force. In this sense, as studied in human chemistry, information or information reception can be understood in terms of field particle exchanges, such as is found in the exchange force that holds human molecules (people) together in human chemical bonds.

Entropy
The original seed of speculation between information and thermodynamics was made in 1894 by Austrian physicist Ludwig Boltzmann who mentioned casually and in passing that entropy is related to “missing information.” (fact check) [7]

In 1928, American electronics researcher Ralph Hartley published the paper “Transmission of Information”, in which he used the word information as a measurable quantity, reflecting the receiver's ability to distinguish that one sequence of symbols (high or low voltages) from any other, in a telegraph transmission, thus quantifying information as:

H = n log S

where S was the number of possible symbols, and n the number of symbols in a transmission. Hartley then concludes with: [8]

“What we have done is to take as our practical measure of information the logarithm of the number of possible symbol sequences.”

In 1929, Leo Szilard argued that the logarithmic interpretation of entropy could be used to determine the entropy produced during the ‘measurement’ of information when Maxwell’s demon discerns the speeds and positions of the particles in his two compartments. As a starting point, Szilard stated that the entropy produced by any random information measurement of the demon could be approximated by: [9]

S = k log 2

On this paper, it seems, in a 1930 letter from American physical chemists Gilbert Lewis, one of the founders of modern chemical thermodynamics, to Irving Langmuir, for instance, Lewis commented that: [3]

“It was not easy for a person brought up in the ways of classical thermodynamics to come around to the idea that gain of entropy eventually is nothing more nor less than loss of information.”

In the 1940s, Hungarian chemical engineer John Neumann suggested to American engineer Claude Shannon that he should called information by the name ‘entropy’ as the reasoning that the equations are similar (they both are in logarithmic form) and that nobody knows what entropy really is, so in a debate you will always have the advantage. In 1948, Shannon took Neumann’s advice and in his famous paper "A Mathematical Theory of Communication", would credit this derivation by Hartley as being the point at which the logarithmic function became the natural choice for information and in the same paper, to the ire of many thermodynamicists, equate Hartley's 1928 telegraph "system" model with that of Clausius' 1865 heat engine "system" model. In short, Shannon, using a similar formulation to that above, declared that H, being a measure of information, choice, and uncertainty, is the same H as used in statistical mechanics, specifically the H in Boltzmann's famous H theorem, concluding with: [10]

“We shall call H the entropy of the set of probabilities.”

Forever after, countless numbers of information theory scientists have since taken any and all types of information, "which is a very elastic term, ... whether being conducted by wire, direct speech, writing, or any other method", in the Hartley's words, as being a direct equivalent to thermodynamic entropy, as derived from the study of the steam engine. In his paper, Shannon would go on to define the entropy H of the source in units of “bits per symbol”, in which in the Hartley derivation s = 2, corresponding to a source that can only send two voltage or current levels, high or low; hence Shannon’s entropy being measured in binary digits per symbol.

This variation of information entropy or “Shannon entropy” has permeated science to the affect that, for some, information is seen as the mediator or key aspect of life and evolution. [5] In 1972, American biophysicist Lila Gatlin stated the following view on entropy and information: [6]


If this statement were taken literally, this would indicate the following relation:

It is difficult, however, to track down the origin of this derivation?

See also
● Entropy (information)
● Information entropy
● Shannon entropy

References
1. Information (definition) – Dictionary.com
2. (a) Thims, Libb. (2007). Human Chemistry (Volume One), (preview), (Google books). Morrisville, NC: LuLu.
(b) Thims, Libb. (2007). Human Chemistry (Volume Two), (preview), (Google books). Morrisville, NC: LuLu.
3. Letter from Gilbert Lewis to Irving Langmuir, 5 August 1930. Quoted in Nathan Reingold, Science in America: A Documentary History 1900-1939 (1981), pg. 400.
5. (a) Brillouin, Leon. (1962). Science and Information Theory (2nd ed.). New York: Dover (reprint).
(b) Campbell, Jeremy. (1982). Grammatical Man - Information, Entropy, Language, and Life. new York: Simon and Schuster.
(c) Avery, John. (2003). Information Theory and Evolution. London: World Scientific.
6. Gatlin, Lila L. (1972). Information Theory and the Living System. Columbia University Press.
7. (a) Shannon, Claude E. and Warren, Weaver. (1949). The Mathematical Theory of Communication (pg. 3, footnote). University of Illinois Press.
(b) Campbell, Jeremy. (1982). Grammatical Man - Information, Entropy, Language, and Life (pg. 44). new York: Simon and Schuster.
(c) Hokikian, Jack. (2002). The Science of Disorder: Understanding the Complexity, Uncertainty, and Pollution in Our World (pg. 57). Los Feliz Publishing.
8. Hartley, R. V. L. (1928). “Transmission of Information”, Bell Technical Journal, July, pgs. 535-64; Presented at the International Congress of Telegraphy and telephony, lake Como, Italy, Sept., 1927.
9. Szilárd, Leó. (1929). “On the Decrease in Entropy in a Thermodynamic System by the Intervention of Intelligent Beings” (Uber die Entropieverminderung in einem thermodynamischen System bei Eingriffen intelligenter Wesen), Zeitschrift fur Physik, 53, 840-56.
10. (a) Shannon, Claude E. (1948). "A Mathematical Theory of Communication" (bit, pg. 1), Bell System Technical Journal, vol. 27, pp. 379-423, 623-656, July, October.
(b) Shannon, Claude E. and Weaver, Warren. (1949). The Mathematical Theory of Communication. Illinois: The University of Illinois Press.

Further reading
● Volkenstein, Mikhail V. (1986). Entropy and Information. Nauka Publishers (Springer, 2009).