Other information theories
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Our information theory is about the creation, use and meanings of messages in social, business and software systems.
This paper mentions other information theories.
This work may be seen as philosophical methodology based on a scientific view of the world.
Especially on biological evolution and the science of digital information systems.
For us, information appears in the act of informing – in the communication of knowledge from senders and to receivers.
The elements of information are descriptive or directive qualities (including quantities).
Our focus is on information created and used in social, business and software systems (which all depend on communication).
And we use the term in relation to messages sent or stored with an intended purpose.
Business systems integration (a focus of enterprise architects) depends on information flowing in messages and stored in memories.
In today’s “information age”, businesses look to capitalise on information they glean from messages transmitted and stored in huge quantities.
So, our information theory is about the creation, use and meanings of messages in social, business and software systems.
It takes a "survival of the fittest" view of how information processing emerged.
It views business systems as formalised social systems, in which actors communicate to cooperate in activities.
However, scientists have developed a broader view of information.
Information Philosophy (I-Phi) <http://www.informationphilosopher.com> is a philosophical method grounded in science.
Especially in modern physics, biology, neuroscience, and the science of information.
And here, the definition of information is very broad.
“The simple definition of information is the act of informing - the communication of knowledge from a sender to a receiver that informs (literally shapes) the receiver.
By information we mean a quantity that can be understood mathematically and physically.
It corresponds to the common-sense meaning of information, in the sense of communicating or informing.
It is like the information stored in books and computers.
But it also measures the information in any physical object, like a snow crystal or a star like our sun, as well as the information in biological systems, including the genetic code, the cell structure, and the developmental learning of the phenotype.
Although some commentators would like to limit the term "information" to messages sent with an intended purpose, physical scientists have long included the structure in physical objects as something that can be measured by an observer and thus is also information.
Information philosophy recognizes material objects as "information structures," from which the pure information can be abstracted as meaningful knowledge.
Information in physical systems was connected to a measure of the structural order in a system as early as the nineteenth century.
Ludwig Boltzmann described an increase in the thermodynamic entropy as "lost information."
In 1929, Leo Szilard calculated the mean value of the quantity of entropy produced by a 1-bit ("yes/no") measurement as S = k log 2, where k is Boltzmann's constant.
Ludwig von Bertalanffy, Norbert Wiener, Claude Shannon, John von Neumann, and others all had similar views of the connection between physical entropy and abstract "bits" of information.”
Claude Shannon developed “information theory” about the limits on signal processing operations such as compression, storage and communication.
Shannon wrote "The fundamental problem of communication is that of reproducing at one point either exactly or approximately a message at another point."
Shannon’s concern was maintaining signal quality in communication; his theory is about the physical content of a message.
Its application in technical communication mechanisms, including the internet, is largely taken for granted by enterprise, system and software architects.
Shannon wrote: "Frequently the messages have meaning"
Any variety in an energy flow or structure of matter is a potential message or signal.
But a signal that is meaningless to any sender or receiver is not a useful concept here.
Some systems thinkers refer to Shannon’s theory in discussion of linguistics and human perception.
But as long ago as 1956, Boulding observed that Shannon did not address the meaning of communication in social systems.
Thanks to Ron Segal for this link http://www.dummies.com/how-to/content/string-theory-and-quantum-electrodynamics.html
"as [two electrons] get near to each other... the two particles communicate their electromagnetic information by emitting and absorbing a photon.
A photon that acts in this manner is called a virtual photon or a messenger photon, because it’s created solely for the purpose of exchanging this information."
Electrons exchange information? Electrons have purposes?
This is a very different domain of knowledge – surely too remote from social and business systems to be drawn into the same conversation.
Today, information processing is seen as essential to all living systems addressed in biology.
“Living is information processing: from molecules to global systems.”
“the whole of life can be viewed… as an integrated information processing system:” (source lost?)
The quoted text below is from a paper by Sara Imari Walker and Paul C.W. Davies.
The Algorithmic Origins of Life, Journal of the Royal Society Interface, 2013, DOI: 10.1098/rsif.2012.0869 (open access)
Which is summarised at http://www.kurzweilai.net/an-information-processing-approach-to-the-origin-of-life.
The authors shift attention from the “hardware” — the chemical basis of life — to the “software” — its information content.
They suggest that the crucial distinction between non-life and life is the way living organisms manage the information flowing through the system.
“We propose that the transition from non-life to life is unique and definable,” said Davies.
“We suggest that life may be characterized by its distinctive and active use of information, thus providing a roadmap to identify rigorous criteria for the emergence of life.
“This is in sharp contrast to a century of thought in which the transition to life has been cast as a problem of chemistry.
“Chemical based approaches,” Walker said, “have stalled at a very early stage of chemical complexity — very far from anything we would consider ‘alive.’
“More seriously they suffer from conceptual shortcomings in that they fail to distinguish between chemistry and biology.
“To a physicist or chemist life seems like ‘magic matter,’” Davies explained.
“It behaves in extraordinary ways that are unmatched in any other complex physical or chemical system.
“Such lifelike properties include autonomy, adaptability and goal-oriented behavior — the ability to harness chemical reactions to enact a pre-programmed agenda, rather than being a slave to those reactions.
“We believe the transition in the informational architecture of chemical networks is akin to a phase transition in physics.
“We place special emphasis on the top-down information flow in which the system as a whole gains causal purchase over its components.
“This approach will reveal how the logical organization of biological replicators differs crucially from trivial replication associated with crystals (non-life).
“By addressing the causal role of information directly, many of the baffling qualities of life are explained.”
Non-local biological functions
“The most important features of biological information (i.e. functionality) are decisively nonlocal,” the authors say.
“Biologically functional information is therefore not an additional quality, like electric charge, painted onto matter and passed on like a token.
“It is of course instantiated in biochemical structures, but one cannot point to any specific structure in isolation and say “Aha! Biological information is here!”
“In all of these cases where appeal is made to an informational narrative, we encounter context- (state-) dependent causation.
“In this respect, biological systems are quite unlike traditional mechanical systems evolving according to fixed laws of physics.
“In biological causation, subject to informational control and feedback, the dynamical rules will generally change with time in a manner that is both a function of the current state and the history of the organism (suggesting perhaps that even the concept of evolution itself may be in need of revision.”
Life in non-organic substrates?
“Purely analog life-forms could have existed in the past but are not likely to survive over geological timescales without acquiring explicitly digitized informational protocols.
“Therefore life-forms that ‘go digital’ may be the only systems that survive in the long-run and are thus the only remaining product of the processes that led to life.
“As such, the onset of Darwinian evolution in a chemical system was likely not the critical step in the emergence of life. …
“Instead, the emergence of life was likely marked by a transition in information processing capabilities.
“This transition should be marked by a reversal in the causal flow of information from bottom-up only to a situation characterized by bi-directional causality.
“Characterizing the emergence of life as a shift in causal structure due to information gaining causal efficacy over matter marks the origin of life as a unique transition in the physical realm.”
Hallmarks of life
The authors suggest these specific hallmarks of life:
· Global organization
· Information as a causal agency
· Top-down causation
· Analog and digital information processing
· Laws and states co-evolve
· Logical structure of a universal constructor
· Dual hardware and software roles of genetic material
· Non-trivial replication
· Physical separation of instructions (algorithms) from the mechanism that implements them.
The standard defines data as the representation of information.
That is aligned with the information theory above; data is a form or matter and/or energy that encodes meaningful information.
(Though saying datum = fact confuses things, since facts sound like meaningful information.)
The standard seems at first to align information with meaning
That is also aligned with the information theory above.
The trouble is, the ISO standard goes on to scramble the idea.
It defines information as knowledge or viewpoint, which is ambiguous and confusing.
If knowledge is the meaning given to some data by an actor - OK
If knowledge only has meaning in a given context - then it
has several possible meanings.
Is knowledge an item of information that can convey several information/meanings?
Or is it an item of data that can convey several information/meanings?
Then, a viewpoint does not integrate data; what integrates data in IS0 42010 is a view.
A view is an aggregate of data elements - a compound data structure.
It may be designed to address the concerns of a stakeholder.
But the meaning obtained from the view is whatever meaning that stakeholder obtains.
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