On information

Copyright 2017 Graham Berrisford. One of about 300 papers at http://avancier.website. Last updated 10/01/2021 16:35


Our main interest is in social and business systems in which actors exchange information.

“connected with system theory is… communication. The general notion in communication theory is that of information.” Bertalanffy

Information passes between actors (inside the system and across its boundary) either continually or in discrete messages/events.

“Even whether the system is closed to energy or open is often irrelevant; what is important is the extent to which the system is subject to determining and controlling factors.

So no information or signal or determining factor may pass from part to part without its being recorded as a significant event.” Ashby 1956


A role of enterprise architects is to observe and envisage information systems

So, you might assume it is universally agreed what a "information" is; but this is far from the case.


Preface. 1

Shannon’s information theory. 1

An information and communication theory. 1

The ubiquity of coding in memories and messages. 1

How memories and messages employ coding. 1

Information, data and knowledge. 1

So, what is information?. 1

Mental models. 1

Communication stacks. 1

Presumptions about language. 1

How do messages/signals differ from meanings/information?. 1

On information in human society. 1

How do social system actors store information?. 1

Does communication imply intention and mindfulness?. 1

Signal quality and interpretation issues. 1

The discreteness of facts in social communication. 1

The digitisation of facts. 1

Abstraction levels. 1

Appendix 1: Other views of “information”. 1

Appendix 2: on the confusion between data and information. 1

Resolving the confusion between data and information. 1

Accepting the confusion between data and information. 1

Appendix 3: Abstracting music from sound. 1





Human life depends on creating, processing, using and sharing information

This is evident from the hundred words (below) we have for doing those things.


Abstracting, Accounting, Agreeing, Analyzing, Answering, Architecting, Asserting, Attributing, Averaging, Believing, Billing, Briefing, Calculating, Characterizing, Chronicling, Coding, Communicating, Composing, Conceiving, Counting, Deciding, Declaring, Decoding, Defining, Demonstrating, Describing, Designing, Directing, Directing, Drawing, Elucidating, Encoding, Envisaging, Equating, Explaining, Expressing, Factualizing, Fictionalizing, Generalizing, Hearing, Hypothesizing, Idealizing, Illustrating, Informing, Instructing, Judging, Justifying, Knowing, Lying, Mapping, Measuring, Messaging, Modelling, Narrating, Observing, Orating, Ordering, Perceiving, Picturing, Postulating, Presenting, Proposing, Qualifying, Quantifying, Questioning, Reading, Recording, Recounting, Reifying, Remembering, Rendering, Reporting, Representing, Reproducing, Sensing, Sorting, Speaking, Specifying, Stating, Story-telling, Summarizing, Testing, Theorizing, Thinking, Totaling, Translating, Transmitting, Truth-telling, Typifying, Understanding, Valuing, Verifying, Viewing, Voting Visualizing, Worrying, Writing, X-raying, Yelling, Zeroing.


The physical forms in which signals can be stored and conveyed, using matter and energy, is not the focus here.

A dash of physics or chemistry might help you understand how information can be stored or conveyed.

But information is better understood in terms of its role in biological evolution and social systems.


It has been said that “all life is information processing”; certainly, information is needed for life.

Even primitive actors need information about the state of the world they live in.

They need to monitor and direct the state and behaviour of themselves and their environment.

An actor’s very survival depends on it perceiving and modelling those realities well enough.

It needs sensors to detect the state of itself and its environment.

Those states must be represented in energy flows sent to body parts or organs.


The ability of actors to describe the world evolved alongside biological evolution.

Evolution led to actors with brains that can remember past facts about the world (e.g. where a food item was buried).

And then to social systems in which animate actors communicate.

“Social” implies actors in the society cooperate, which in turn implies they communicate, share information using a common language.

“System” implies actors in the system follow given rules when responding to information received.


Social systems, information and communication existed before human actors,

However, the range of communicable information vastly increased with the ability to describe things in a verbal language.

Humans use a wide variety of signals to share information that describes things, which they need to monitor or direct.

They create information by organising matter. E.g. by writing a letter, or painting a picture, or placing a chess piece.

The retrieve information from organised matter via energy flows. E.g. the light reflected from a painting or chess board.


Social systems range from the informal to the formal.

In evolutionary terms, business systems evolved from social systems.

Humans formalised social communication to standardise the transactions of government and commerce.

In short, information existed eons before human and computer activity systems.

Shannon’s information theory

Claude Shannon’s information theory is about the journey of a signal or message from sender to receiver.

Shannon wrote: "The fundamental problem of communication is that of reproducing at one point either exactly or approximately a message at another point."

The theory addresses limits on signal processing operations such as compression, storage and communication.


Shannon also wrote: "Frequently the messages have meaning".

The signal/meaning distinction may be drawn thus.

·       A signal is matter/energy organized such that actors can detect structures/variations in it.

·       Signals appear in physical messages and memory structures.

·       Meanings are created or found by actors in signals.


However, as long ago as 1956, Boulding observed Shannon did not address the meaning of messages.

Traditional information theory does not address what is expressed (descriptions, directions or decisions) in writing or reading a signal.

So, how to ensure a receiver extracts the same meaning from a signal that the sender intended to convey?


Some approach meaning from the viewpoint of a linguist – assuming meanings are expressed in verbal ways.

But meanings are found elsewhere - in non-verbal signs and in the after effects of behaviors.

In fact, meanings arise when and wherever an actor finds any usable information in any structure or behaviour.


This article is not about Shannon’s information theory!

And we don’t begin here by thinking of information like a linguist or software engineer might do.

Millennia before verbal languages and computing, animals encoded input signals into memories.

Then decoded memories into the stream of consciousness when determining responses to events.

And social animals encoded and decoded messages (e.g. alarm calls) without needing to learn a language.


Try to imagine how you’d mimic these incredibly effective processes in software.

Inevitably, you’d find yourself drawn down paths you understand.

You’d think of data structures - stored in databases, and transmitted in data flows.

You’d presume the need for formally defined languages, symbols, syntax and semantics.


But surely, a truly general information theory cannot start from or depend on how software works?

It ought to start from the evolution of information created and used by animals

Many animals can not only remember information internally in memories, but also share information messages.

An information and communication theory

Theorists have defined “information” in a variety of ways.

In "The Information: A History, a Theory, a Flood" James Gleick presents a pot pourri of views about information.

The general conclusion is that information is “anything that could be discerned”.

That is, any structure/variation in matter/energy.

Similarly, a philosopher has written that information is “any quantity that can be understood mathematically and physically.”

That is, any snowflake, star, organism and genetic code is an "information structure".


Here, the interest is in structures that are intentionally created to represent information.


Information: a structure or behavior that represents something or phenomenon.

More scientifically: “A carries information about B if the state of A is correlated with the state of B.”

Animals can hold information in memory and communicate it in messages.

In our triangle, the information at the apex embraces both memories and messages.


Intelligent life

Memories and messages

<create and use>          <represents>

Animals      <observe and envisage>    Phenomena


Memories and messages: holders of information.

In biology, internal memories and external messages are of different kinds.

Memories are neural patterns; messages take the form of sounds, smells and gestures.

In software, the distinction between memories and messages is blurred.


Communication: the exchange of information between senders and receivers.

Actors may exchange information directly by sending/receiving messages.

Or else, indirectly by writing/reading information stored in some memory both can access.

They respond to information in messages, often in a way determined by information in memory.


Social communication

Information in messages

<create and use>             <represents>

Communicators  <observe and envisage>  Phenomena


Remember: “A carries information about B if the state of A is correlated with the state of B.”

A message represents a phenomenon if the structure of the message can be correlated with some features of the phenomenon.

The ubiquity of coding in memories and messages

Ashby was interested in how information is stored and communicated.

In the processes of creating and using information, rather than its physical form.

These processes encode and decode information into and out of physical forms.


Ashby observed that in the creation and use of information “coding is ubiquitous”.

To create information is to write or encode a model that represents something.

To use information is to read or decode a model, and use it for some purpose.


Nobody understands how conscious knowledge is encoded in and decoded from our biochemistry.

But evidently, those processes exist.

Suppose you ask me to look at the moon.

·       Your thought is encoded in neural impulses, then vocal chord movements, then sound waves.

·       Then from sound waves to my ear drum movements, to neural impulses.

·       Then to conscious thought in my mind which can be encoded in my memory.

During the communication, the idea is expressed or encoded in various forms, public and private.


Ashby presented this longer example.

“Let us consider, in some detail, the comparatively simple sequence of events that occurs when a “Gale warning” is broad-cast.

It starts as some patterned process in the nerve cells of the meteorologist, and then becomes

·   a pattern of muscle-movements as she writes or types it, thereby making it

·    a pattern of ink marks on paper. From here it becomes

·    a pattern of light and dark on the announcer’s retina, then

·    a pattern of retinal excitation, then

·    a pattern of nerve impulses in the optic nerve, and so on through her nervous system. It emerges, while she is reading the warning, as

·    a pattern of lip and tongue movements, and then travels as

·    a pattern of waves in the air. Reaching the microphone it becomes

·    a pattern of variations of electrical potential, and then goes through further changes as it is amplified, modulated, and broadcast. Now it is

·    a pattern of waves in the ether, and next

·    a pattern in the receiving set. Back again to

·    a pattern of waves in the air, it then becomes

·    a pattern of vibrations traversing the listener’s ear-drums, ossicles, cochlea, and then becomes

·    a pattern of nerve-impulses moving up the auditory nerve.


… this very brief account mentions no less than sixteen major transformations

through all of which something [the intention] has been preserved,

though the superficial appearances have changed almost out of recognition.” (1956, 8/2)


To send and receive the gale warning message involves a succession of coding and decoding steps.

The message is passed down and up a communication stack.

After receiving a message, a listener can verify the accuracy of the warning by watching the weather.

How memories and messages employ coding


Representing a structure

Suppose A = a map and B = a territory.

And there are correspondences between the structures of the two entities.

Then the map carries some information about the territory.

And the territory carries some information about the map.

Representing a behavior

Suppose A = a musical score and B = a musical performance.

And there are correspondences between the structure of A and the behavior of B.

Then the musical score carries information about the process of the performance.

And the performance carries information about the structure of the musical score.


Remembering a thing


·       A = the state of something in the environment.

·       M = the state of a message conveyed by eyesight to your brain

·       B = the state of a memory in your brain.


To register and remember the existence of the thing

·       A is encoded into M

·       M is decoded and encoded into B.


Ultimately, the meaning of a memory is not found in the memory alone.

It is found in the process by which B is decoded by retrieval and used.

This last is the information of most interest to psychology.


Communicating an idea


·       A = the state of a message sender’s brain.

·       M = the state of the message.

·       B = the state of a message receiver’s brain.


To communicate an idea

·       A is encoded in M

·       M is decoded and encoded into B


The aim of human-to-human communication is not to draw a biological correspondence between A and B.

How far the structures of two brains can be correlated at the biological level is unclear.

By contrast, correspondence at the sociological level can be observed and verified.

Information, data and knowledge

In natural language: the terms data, information and knowledge are often used interchangeably.

To facilitate discussion of social systems, an informal classification is helpful.

Several WKID hierarchies have been proposed and criticised.

The version below seems the best fit to a system of communicating actors.





the ability to apply knowledge in new situations.


information that is accurate enough to be useful.


meaning created/encoded or found/decoded in data by an actor.


a structure of matter/energy in which information has been created/encoded or found/decoded


Any physical structure of matter or energy can be used as a data structure or signal.

It becomes a data structure when the structure encoded to convey information/meaning.

And when it is decoded as conveying information/meaning.



Any structure or motion that is variable - has a variety of values – can be used to store or convey information.

E.g. You may use

·       The biochemical structures your brain.

·       The shadow on a sundial - to represent the time of day

·       The state of your office door (open or closed) - to tell people whether you are open to visitors.

·       Dance movements - to express emotions.


Here “structure” embraces both data structures and process structures like dance movements

And marvellously, humans can form countless structures in the form of words, with almost no physical effort.



There is no information or meaning in a structure on its own.

Data creators must perform processes to encode/create meanings in structures.

And data users must perform processes to decode/find meanings in structures.


This “information” of interest to sociology only exists in those processes.

In the intentions of data creators and the interpretations of data users.


Why draw a data/information distinction at all?

This data/information distinction is a subtle one.

In business systems, the terms are usually interchangeable.

It is taken for granted that receivers decode meanings that senders intended to encode.

Because messages are transmitted perfectly (where Shannon comes in).

And to write and read messages, senders and receivers use the same language.


The distinction matters little where a signal/message conveys the same meaning to all receivers.

A communication theory has to deal with exceptions

Where the data in one signal/message conveys different information to different receivers/readers.

And where where the information potential in a structure or motion can yield legitimately result in different meanings.

For example, the movement of the sun across the sky has information potential.

It becomes actual information when used by a sunflower to turn its face, or a sundial reader to tell the time.

So, what is information?


The order in a structure has information potential

There are infinite structures in the matter/energy of the universe.

Every structure has some order, as opposed to disorder or entropy, and some scientists say that the order in a structure is information.

Here, the order in a structure has information potential to actors.

And our concern is how actors interact by creating and using information.

The medium for information exchange is a matter/energy structure of some kind.

Many animals use sound waves (calls), smells or gestures.

Humans use sound waves (speech), written text, flags, radio waves and other media.


Information has at least one sender and/or receiver

Let us call actors who create information senders, and actors who consume information receivers.

Sometimes (as a voice crying in the wilderness) a sender creates information in a message or memory structure that no receiver inspects.

More curiously, sometimes, a receiver finds some information in a structure that was not intentionally sent.

The sun radiates a flow of light towards a rotating earth.

One man concludes that the sun rotates around the earth, another that the earth spins on its axis.

Another reads a sundial as telling the hour of the day.

A sunflower finds a direction to turn its face to optimise its energy consumption


Information is shared using languages

Our concern is how actors interact by creating and using information.

The meaning of the information can include descriptions, directions, decisions and requests for them.

Senders encode information in message and memory structures, and receivers decode information from them.

We tend to presume that receivers will find in a structure whatever information senders intended to create.

But the sharing of information depends on two things.


Message and memory structures must be preserved between sender and receiver (cf. Shannon’s information theory).

E.g. Speaker says: “Send reinforcements we are going to advance.”

Listener hears: “Send three and four pence we are going to a dance.”

The intended signal is distorted at some point between sender and receiver.


Creators and users must share the same language for encoding and decoding, or can translate perfectly between languages.

The fuzziness and fluidity of natural language often leads to a miscommunication.

E.g. Speaker says: “He fed her cat food.”

Listener 1 hears: He fed her cat – food (He fed a woman’s cat some food).

Listener 2 hears: He fed her - cat food (He fed a woman some food that was intended for cats).

Listener 3 hears: He fed - her cat foods (He somehow fed the cat food that a woman owned).


Information is a subjective view of a structure.

There is no information in a structure independent of senders and receivers and the languages they use.

E.g. what information is there in the position of my office door?

Case 1: I leave my office door open to signal that I am open to visitors; you read the door as saying I am open to visitors, and enter my office. OK

Case 2: I leave my office door open by accident, but am open to visitors anyway; you misread the door as saying I am open to visitors, and enter my office. OK

Case 3: I leave my office door open by accident, but am not open to visitors; you misread the door as saying I am open to visitors, and enter my office. Not OK.

Case 4: I act as in any case above; you close door. OK or not?


There is no information in a structure per se.

Information exists only at the moment a sender or receiver uses a structure as information.

Any structure becomes a signal if and when a receiver decodes a structure as conveying information.

OR a sender creates the structure with the intent to encode information in it.

Information lies not in the structure itself, but in the decoding and encoding processes.

E.g. the structure in DNA becomes information when it is decoded.

It may be decoded by a biological cell as instructions for making proteins.

Or decoded by human decoder of the genome as carrying a gene for some life-shortening condition.

Neither actor can read and act on the structure as the other does.


Knowledge is information that is true enough to be useful.

If I say the sky is blue when it is cloudy, you still find information in my message, if only the information that I am a liar.

What a sender considers true, a receiver may consider false, and vice versa.

Sometimes what we say can be tested by measurement of meaning against reality.

But all measurement has a degree of accuracy, and even Newton’s laws of motion are approximations.


Any meaning a sender or receiver creates or finds in a message or memory structure is information to that actor.

The accuracy or truth of information is a matter of degree.

Knowledge is information that is true enough to be useful (e.g. Newton’s laws of motion).

Mental models

A mental model is some kind of memory, against which a new perception can be matched.

If two actors find the same information in a perception, then they must share mental models well enough.

(They share their logical readings/understandings of their mental models, rather than share their physical brain matter.)


Consider two actors looking at the shadow of a person cast on a cave wall.

If the two actors reckon a shadow describes a man’s outline, they must share much the same mental model of a typical man’s outline.

If both recognise the particular man whose shadow is cast, they must share the same mental model of that particular man’s outline.


Suppose one actor reckons the shadow is of a man, and the other actor says the shadow is of a woman.

The shadow is not the information – it has no meaning on its own

Its meaning depends on how well it matches a mental model

These two actors do not share mental models well enough to find the same information/meaning in the shadow.


One signal or data form can mean different things to its creator and its consumers.

(Enterprise data architecture is partly about ensuring all creators and consumers attribute the same meanings to the same signals/data forms.)

Communication stacks

In a communication stack, logical information/meaning is encoded in physical messages/signals at successively lower levels.

And in reverse, a physical signal is turned into logical information at successively higher levels of abstraction.


This table is an attempt to explain the receipt of a message using the Morse code communication stack.

Read it from bottom to top.


Logical - sentences

human reads word groups as sentences giving meaningful directions or descriptions


Logical – words

human reads character groups as words


Logical - characters

human reads impressions on the paper tape as characters


Physical - encoding

armature impresses indentations onto a paper tape


Physical - force

electromagnet pushes armature


Physical - energy

telegraph wire delivers pulses of electric current to an electromagnet


In a typical communication stack:

·       the top is the level of logical human thinking;

·       the bottom is the level of binary digits represented in some kind of physical form.


The physical base from which information can be abstracted might be electrical charges.

Everything above the physical medium is meaningful information abstracted by an actor of one kind or another.

Computer actors to abstract logical 1s and 0s from physical electrical charges.

At higher levels, others actors (or the same actor) can decode richer meanings from composites of 1s and 0s.


Our primary concern is with the meaning understood by human senders and receivers of information.

But every machine lower down a communication stack works at its own level of meaning.


Also, the top level of a communication stack does not have to be either human or verbal.

A machine (as in an embedded process control system) can find the meaning in a signal and act accordingly.

Presumptions about language

The language used to encode/decode information in data is composed of a vocabulary and a grammar.

The same vocabulary may be expressed in many forms: spoken words, Morse code, sign language or other gestures, and digital messages and records.


People hold mental models that describe realities

(The bio-electrical-chemical form of a mental model is irrelevant here.)


These mental models are fuzzy and flexible - as they need to be

Evolution and learning make them merely accurate enough for us to direct our actions successfully.


Some animals use the vocabulary and grammar of a language to

·       encode mental models into physical forms

·       decode from physical forms into mental models

Encoding a mental model in a physical form is a way to make the model more stable and shareable.


We attach words to discrete perceptions,

At the macro scale, reality is continuous; even solid/liquid/gas phase divisions are fuzzy-edged

But we perceive reality as chunks discrete in time and space; and we attach words to those chunks

Which works well enough for us to direct our actions.


Is a verbal proposition inherently true or false?

“The sky is dark today”

The meaning of a verbal proposition depends on the language (v & g) applied to it and the context it is used in

A proposition may be true enough to be useful to one person and not to another.


Which linguistic philosophy do we agree with?

Formalist, Non-formalist, Structuralist, Post-structuralist or Deconstructionist?


Here, natural language is no more than a side effect of biological evolution

It is inherently messy and ambiguous

It is ill-suited to perfect, unambiguous communication

It is just good enough to aid survival.


However, natural language has been refined by people in business, science and mathematics who strive to model the world more coherently and consistently.

Business systems use domain-specific languages that formalise natural languages well enough for businesses to survive.

Software systems formalise domain-specific languages further.

How do messages/signals differ from meanings/information?

Here, information is meaning created or found by an actor in some matter or energy that acts as a signal.

There is information potential in any variety detectable in a structure of matter or flow of energy.

There is actual information when actors use some information potential to recognise or describe something, or direct some action.


There is information potential in the variable

There is actual information when

angle of the sun’s rays.

a human reads the time from the shadow on a sundial.

a sunflower perceives the position of the sun and turns to face it

nerve impulses (electrical charges).

an actor responds by removing its hand from a hot plate

bending of a bi-metal strip.

a thermostat responds by switching a heater on or off.

movements of a honey bee.

honey bees dance to communicate a location of pollen.

open or closed state of an office door.

actors share a vocabulary in which an open door means “you have permission to enter”.

lengths of dots and dashes (in sound, light, braille…)

actors use Morse code to communicate.

quantity in a number.

an actor says 20 in reply to a request for a fact (say, the speed of a bicycle in miles per hour).


The last four examples are social systems in which senders and receivers benefit from sharing the meanings in signals.

Signal senders encode logical meanings in physical forms; signal recipients decode logical meanings from physical forms.

Information is created in the act of encoding meanings in signals, and obtained by decoding meanings from signals.


A social system depends on its members sharing information.

System actors must communicate by sending and receiving messages or signals.

All the actors in this paper are message senders or receivers (in evolutionary terms, computer actors are proxy human actors).


The system can only thrive if actors find the same meanings or information encoded in the signals they send and receive.

Actors create and find logical information in a physical signal by mapping its elements to a general pattern or language.


With no actors to look at it, a message (be it print on paper or magnetic patterns on a disc) it is just an arrangement of matter and energy.

The meaning of the message lies in the intention of the sender and the interpretation(s) made by receiver(s).


Different actors may find different meanings in one message.

When and where do those two meanings exist? Not simply in the material form of the message.

No actor can understand the material form of a message without a language, or be entirely sure how it might be interpreted by another.

Meanings arise at moments when actors create and interpret a message.

They do this by mapping elements of the message to a language known to the actor.


These three messages may help to further illustrate the difference between signals and meanings.

·       “Read the symbols in this signal.” Since the signal quality is OK, and we share the same language, you’ll read the meaning I intended.

·       “Read thu simbuls in this signal.” The signal is different (the quality is imperfect), yet the meaning you read is surely the same.

·       “A rose is a rose is a rose.” The signal is intended to be meaningless, yet you may nevertheless find some meaning of your own in it.

In other examples, ambiguities arise from the use of ambiguous words, or different dialects of a language.


In short, information is meanings created and found in messages or signals, by actors using a domain-specific language.

Social systems depend on messages – usually - conveying the same meanings to message creators and users.


What do meanings mean? Often, they are directions or descriptions.

Directions may be continuous or divided into discrete instructions.

Descriptions are usually divided into facts (tasty, tall, scary) about things (say, food, friends and enemies) that actors perceive as discretely identifiable.

On information in human society

How do social system actors store information?

In evolutionary terms, all information storage must have started off as fuzzy and imprecise.

Biological memory mechanisms are fragile, prone to error, decay and loss.

Humans evolved the ability to communicate logical information using physical sound waves.

Then to store information (including the state, languages and rules of a social system) in persistent storage materials.


In 2,500 BC Sumerians stored their literature, laws (behavioural rules) and business transactions (information) in libraries of clay tablets.

(Sumerians had shifted from picture-writing into cuneiform, which means "wedge writing" in Latin.

Cuneiform was written with a wedge-shaped stylus, similar to ones used on today's hand-held computers.

Writing was inscribed into damp clay tablets, which were then baked until hard.)


A social system’s state also includes the current state of inter-actor communications.

A request-reply communication requires that signal creators and users share a language.

But moreover, the requester must remember the question to which an answer is sought, and associate any reply with that question.

So, social communication requires that a requester’s brain remembers the state of an inter-actor request-reply communication.

And in this way, the current state of inter-actor communications is distributed between the minds of social system members.

Does communication imply intention and mindfulness?

Information can be extracted from a signal, even though the sender had no intent or mind to send a message.

When you read the time from a sundial’s shadow, you don't attribute any intent or mindfulness to the sun.

(Though the creator of the sundial was mindfully intent on building it to block the sun’s rays.)


However, our focus is on social/business systems in which messages have both senders and receivers

Some receivers may not successfully obtain the meaning intended by the sender.

But a social system's very survival depends on enough receivers sharing senders’ intended meanings.


Words like "intent" and "mind" are questionable in a general information theory.

You might say a human, elephant or dog "is minded" or "intends" to send a message, within or across species.

You might feel uncomfortable about saying the same of a bee or an ant.

You probably see honey bees as automata without minds or intentions to do things.


It seems our concept of mindfulness is tied up with the self-awareness we see in at least some animal species.

And it seems reasonable to speak of "intent" and "mind" where social system members are self-aware.


By the way, some regard as jellyfish as social system all to itself.

(At a brief glance, "The Social Metabolism: A Socio-ecological Theory of Historical Change" by Manuel González de Molina Navarro, Víctor M. Toledo looks relevant here.)

Signal quality and interpretation issues

The physical content of a signal can be written and read with different meanings – accidentally or deliberately.

To repeat the example above:

A general tries to say “Send reinforcements; we’re going to advance” using the physical medium of sound waves.

A corporal hears the same physical signal as “Send three and four pence; we’re going to a dance.”

Thus, the signal receiver obtains information, but not the information the signal sender intended to convey.


Humans and computer actos can use Morse code to code/encode meanings in a physical signal.

Suppose senders and receivers use different versions of Morse code, then they will write/read different character strings.

At the first level of decoding, the signal receiver can read the message as a character string – with no apparent difficulty.

But at the next higher level of reading, the receiver will find it the characters do not form into words.


A poet may say their poem means (signifies) whatever meaning each reader finds in the poem.

Some systems thinkers take that idea to an extreme.

They say that meaning is only found after a signal event – in the use(s) made of the signal.


This way of thinking about communication may lead you to Luhmann's "autopoietic social system."

There are reasons to doubt the value of Luhmann's theory.

First, it radically changes the meanings of “autopoiesis”, “society” and “system” understood by others.

More importantly, society depends on listener/readers (usually) successfully construing what speaker/writers mean.

This means signal senders and receivers give the same meaning to the contents of signals.

This implies the actors must share a vocabulary and grammatical rules – be they innate or learnt.

The discreteness of facts in social communication

The universe may be continuous, but animals do decode apparently continuous signals into discrete facts.

Honey bees watch a dance and decode it as showing the distance and direction of a pollen source.

You see a rainbow as distinct bands of colour; you hear a continuous stream of sound as composed of discrete words.

You perceive a stream of light as revealing your lunch to be collection of discrete food items sitting on a discrete plate.

Discriminating between these things is useful; it helps you to spear discrete food items and eat them.


“At a conscious level, humans tend to interpret the world as discrete things.

We pattern match, then label (not necessarily verbal), then move our limited attention on, which is part of a survival strategy, to categorise things as safe or dangerous.

'Chunking' may better describe the operation (https://en.wikipedia.org/wiki/Chunking_%28psychology%29 ).

Most descriptions of chunking don't do justice to the profound way in which it avoids information overload.” Ron Segal


How our brains and computers work at the neuron or electronic level is not important here.

At the level of consciousness and social communication we chunk our perceptions of the universe into discrete entities

Perceiving and describing discrete entities (you, me, your lunch, or a bicycle ride) is how we make sense of the world.

And we describe those entities in terms of discrete facts (you are tall, I am old, lunch is tasty, and this bicycle is speeding at 20 mph).

These descriptions are models or coded representations of the states of things we perceive as discrete entities.


If a signal can be perceived as composed of elements, then each element may be used to convey unitary fact (e.g. surname).

You can create or find composite facts in a structure of elements by matching it to the rules of a grammatical structure.

E.g. full name = forename + list of middle names + surname.

The digitisation of facts

The term analogue is used to describe signals or data that vary continuously, as the hands on a clock face do.

The term digital used to describe signals that are chunked into discrete units, as you read from a clock that displays discrete numbers.

It is now common practice to convert continuous analogue signals into discrete digital signals, and vice versa.


The entry to the information age was associated with the digital revolution that happened as business communications were computerised. 

Most communications are now sent and received by computers in a binary digital form.

This means that information is encoded in signals/data flows using the binary number system as series of discrete digits 0 and 1.

The binary digits may be represented in physical signals as the presence or absence of physical things.

Or as the contrasting values of a physical quantity such as voltage or magnetic polarization.


How to encode human-level verbally-expressed information in binary digits, and decode information from binary digits?

This is usually done step-by-step, in a series of transformations, down and up a communication stack.

Abstraction levels

The table below shows three levels of abstraction away from the behaviour of entities in the material world.

At each level, actors create and use data that conveys information from or to actors at the level below.


At this level of abstraction

these actors

work to

and so convey information about 

3 meta system


define notations for modelling data and process structures

The language systems designers use at the level below

2 system description

system designers

define data types and process flows that using the notations above

The language systems actors use at the level below

1 operational (run-time) system

system actors

read and write messages containing data items conformant to data types above

The attributes and behaviour of real entities at the level below

0 material (run-time) world

external entities

do stuff that is describable in messages above


Appendix 1: Other views of “information”

This work may be seen as philosophy 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).


However, a message that is not actually meaningful to any sending or receiving actor is not a useful concept in this work.


Social, business and software systems all depend on communication.

Our focus is on information created and found in 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 that have been stored in huge quantities.


Our information theory takes a "survival of the fittest" view of how information processing evolved in social systems.

It views business systems as formalised social systems, in which actors communicate to cooperate in activities.


For us, the fundamental problem of communication is that of knowing what a message means, at a logical level.

A system can only thrive if actors who receive messages/signals find the same meanings/information that senders encoded in those messages/signals.

And this can only happen if senders and receivers both map elements in messages/signals to elements in a shared language.

To create and find logical information in messages and memories, actors must map discrete elements to elements types in a shared language.

Appendix 2: on the confusion between data and information

This morning (28/10/2015), I received the email below from a recruitment consultant.

Enterprise Information Architect: London - £90,000 per annum plus benefits.
My client, a large and iconic London brand is now looking for an innovative and experienced Enterprise Information Architect.

He/she will focus on developing and leading the exploitation of data and information architecture in conjunction with business area leads, business partners and project delivery teams.


How does the recruiter expect us to differentiate information from data?

Consider a particular telephone number, or customer address. Is that a data item or an information item?

Consider a message containing customer name, address and telephone number. Is that a data message or an information message?

Does it make any difference who creates the item or message - a human or a computer?


Consider the generalised structures for items and messages – simple data types and complex data types or data structures.

Consider the structure for a telephone number, or an invoice. Is that a data type or an information type?

Does it make any difference whether the type is defined by an international standards body or by a programmer?


Consider the higher level meanings of messages that are created in message by senders and obtained from by receivers.

Does it make any difference who creates the item or message - a human or a computer?

Resolving the confusion between data and information

Business system design usually addresses the plural (sets of things) rather than the singular (individual thing).

Business processes follow the logical paths defined in general process types.

Processes monitor and direct business entities and events that instantiate defined types.

Messages convey meaningful information about business entities and events by giving values to their typical qualities.


A business needs senders to encode meanings in messages, and receivers decode the same meanings from those messages.

To this end, the mapping of data types to generalised meanings must be agreed and defined before messages are sent.

Thus, business systems formalise what is fuzzy and ambiguous in purely social communication.

Social system members may share their own language for describing the entities and events of interest in their domain.
The domain-specific language used in a digitised business system is commonly defined in what is known as a ontology

A data model is an ontology composed of generalised data types (e.g. Customer, City) instantiated as data items (e.g. Jack Jones, London) in particular messages and records.

This language stands apart from, is independent of, particular actors, particular signals, and particular information.


The proposal here is: Data is a signal or signal element that can be created or perceived by an actor, and mapped to a general language or ontology.

Honey bees use the language of dance to signal the locations of pollen sources; situation-specific data is found in particular dance movements.

The bees’ language is generalised; it is independent of particular bees, particular dances and particular pollen sources.

Accepting the confusion between data and information

So, why are the terms “data” (signal) and “information” (meaning) so confused in enterprise architecture?

Because systems are built on the assumption that physical data carries the same logical information to all senders and receivers.

It is assumed that the meaning actor A gives to data on posting it will be read with the same meaning by actor B, in a different time and place.

And that data stores record the current state of business entities (and/or the history of business events) in a shared memory all understand the same way.


In practice, the term data and information are used interchangeably and used so loosely.

You generally can’t assume either term has any one specific meaning.

Some equate data with information; some equate data with signals.

(A sister paper called Data, Information and Knowledge addresses the wide variety of ways people distinguish the terms.)

Appendix 3: Abstracting music from sound

The universe is an ever-unfolding process, in which space and time are continuous.

But our perceptions and descriptions of phenomena divide continuous things and qualities into discrete chunks.

E.g. thousands of years ago, musicians divided the continuous spectrum of sound into discrete notes.

Now, anybody who enjoys music divides the continuous spectrum of sound into discrete and different notes.


In music, a pure note is a sound of one frequency only.

A vibrating string sounds a note; the shorter the string, the higher the note.


The overtone series

Suppose you divide a long string in two, then three, then four, then five, and so on.

Successively smaller strings sound ever higher notes - which are harmonic overtones of the original string.

A musician can mimic this progression by playing the notes below on an instrument (starting on C).









major third


minor third


sub minor third



















Frequency ratio

1 to 2


2 to 3


3 to 4


4 to 5


5 to 6


6 to 7


8 to 9



Continue the series forever, and you will discover infinite notes.

Each division sounds a higher note, but the gaps between them get smaller and smaller.

Some notes are the same as earlier ones, or so close to earlier ones they are named the same in the sequence below.





























Distributed among 26 overtones, are the 12 notes (blue below) you can discover in “the cycle of fifths”.
























































The cycle of fifths

You discover the same 12 notes if you follow the “cycle of fifths” (2 to 3 intervals) from C until you return to C.
















The two series above explain why musicians divide the continuous spectrum of sound from C to C’ into those 12 discrete notes.

On a key board, the notes are sequenced in one octave, divided between two scales playable on the white and black notes.


The scale on a key board has 12 different notes














A diatonic scale on the white notes has 7 notes














A pentatonic scale can be played using the 5 black notes















The intervals between the 12 notes are all called semi-tones.

In the major diatonic scale shown, the intervals are whole tones, except E, F and B, C which are semitones.


The just intonation scale

The just scale (or harmonic tuning) occurs naturally as a result of the overtone series above.

Almost every pair of notes in the scale (forming a two-note chord or arpeggio) is related by simple frequency ratios.

The most common simple ratios are 1 to 2, 2 to 3, 3 to 4, 4 to 5, 5 to 6, 6 to 7 and 8 to 9.

And being simple ratios, they sound reasonably smooth or consonant.


Just tuning is often used by choirs, as the singers match pitch with each other "by ear."

However, this most natural scale is uneven; the gaps between semitones go up and down in a curious way.

The result is that a diatonic scale that starts on any note but C sounds wrong.

The tuning depends on the scale - the tuning for D Major differs from C Major, and so on.


The even-tempered scale

To play in different keys, musicians invented well-tempered (17th century) and equal-tempered (20th century) scales.

The equal-tempered scale was developed for keyboard instruments, such as the piano

It is a compromise tuning scheme, using a constant frequency multiple between the notes of the chromatic scale.

Hence, playing in any key sounds equally good (or bad, depending on your point of view).

Only keen musical ears notice the difference between music played in just and even-tempered scales.


In short, we abstract music from sound, we abstract the psychological from the physical

For more, try https://pages.mtu.edu/~suits/scales.html