Keywords: Definitions, Data, Information Theory, Meaning

Citing this page:

Jones, P. (1998) Hodges' Health Career - Care Domains - Model, Defining Information

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Introduction

We live, it is said, in the 'information age'. A moments reflection, however, might suggest that these times are in fact in the 'data' age - with the true information age just around the corner. From the dialogues of Plato (What is knowledge?) to the present day, questions about the nature of knowledge have perplexed philosophers for millennia. Since Plato's age enlightenment has waxed and waned, it is only since the digital age that our preoccupation with knowledge, data and information has exploded.

Together cognitive science and information science have given rise to whole new areas of ontological study, and in related fields such as search and retrieval. The digital age is prompting new, radical definitions of information. Devlin (1991) backtracks a little to address the need for a definition of 'perception'. This is defined as a two stage process, corresponding to an analogue/digital distinction:

'The first stage is perception, where the information in the environment becomes directly accessible to the agent by way of some sort of sensor ... At this stage the information flow is analogue, relative to whatever information we are concerned with. The second stage, if there is one, involves the extraction of a specific item (or items) of information from that perceived 'continuum'; that is to say, it involves the conversion from analogue to digital information. This stage is cognition.'

INFORMATION about DEFINING DATA

Despite emphasis upon 'analogue' and 'digital devices', 'data gathering', 'CPUs', 'flowcharts', 'resource management', and other 'infospeak' little is understood about data and information. Everyone uses it, but what is information? Scarrot (1987) and Stamper (1985) posed this question, which businesses are often forced to ask as they seek to realize benefits from ICT. Bawden (1992) defines information as the fourth "corporate resource".

During the mid-1980s, the microcomputer boon gathered pace, three pivotal applications - wordprocessing, spreadsheets and databases - were becoming accessible to more non-specialist people. Commentators at this time pointed out that despite references to 'information theory', there was in fact no 'theory of information'. Editorial (1985) Some proposed that the beginnings of a theory of information existed, but much needed to be done. Hamming (1980) wrote;

"Information theory does not handle the meaning of the information, it treats only the amount of information.." and "The applicability of the ideas is not exact - they are often merely suggestive - but the ideas are still very useful. ... ; the theory provides an intellectual tool for understanding the processing of information.".

So how far has our understanding progressed? What is data, information?

Data is usually regarded as the most fundamental form of information. A symbol e.g. 'a', 'y', 'K', '6', '%', '+', or a signal can all be viewed as data. Usually the term 'data' suggests something raw and unrefined. Something that must be polished into a finished product. Researchers actually talk of 'cleaning' their data. Data in machine readable form may be unintelligible to people, for example, barcodes and sensor readings. Currently, as defined by their operation, computers process data they do not (yet) process information. Specific words - such as a person's name - are usually considered 'information'; while a person's hospital number is usually viewed as data. Despite this the terms 'data' and 'information' are often used synonymously.

For example, a collection of data items commonly called a 'data set' may in fact include information. Executives 'mine' the data in their corporate databases. What they seek is information, hidden in vast quantities of data. Information usually denotes data, in a combined form used for some specific purpose. So people speak of the database, from which the report is produced containing the information required. Further complexities are found when information is encoded. What looks like 'data' as I have just defined could in fact be information, as described below.

Despite the advent of the information age there is no clear and precise definition of information. Those definitions that have emerged, however, are remarkable in their underlying simplicity and potential scope of application. Furthermore, they are especially interesting when applied to health related disciplines. A classic, and much cited text in communication theory is - 'A Mathematical Theory of Communication' by Shannon and Weaver (1949). Weaver's contribution is quite accessible to non-mathematicians (like the author of this paper), while Shannon concentrates on the mathematics of telecommunications. Weaver provides the following definition of information:

'.. this word information in communication theory relates not so much to what you do say, as to what you could say. That is, information is a measure of one's freedom of choice when one selects a message. If one is confronted with a very elementary situation where one has to choose one of two alternative messages, then it is arbitrarily said that the information, associated with this situation, is unity.' pp.8-9

Work continues under the flag of 'information theory', which is concerned with the processing of information, its constitution, transmission and properties. Drekste (1981) writes:

'Information theory identifies the amount of information associated with, or generated by the occurrence of an event (or the realization of a state of affairs) with the reduction in uncertainty, the elimination of possibilities, represented by that event of state of affairs.' p.4

COMPUTER SCIENCE AND INFORMATION

The well known fiction author Umberto Eco (1976), has also written valuable contributions on information. Eco offers two basic senses for the term 'information':

'A) 'it means a statistical property of a source, in other words it designates the amount of information that can be transmitted; B) it means a precise amount of selected information which has actually been transmitted and received.'

The definitions just cited can be threaded together. Mention of 'choice' and 'amounts' of information occurs in each definition, so the next question arises logically. How can this 'thing' called information be measured? Drekste cites an example of eight employees who must select from amongst themselves which individual is to perform some unpleasant task.

For example, one nurse must clean a trolley, and there are eight candidates (or non-volunteers!). There are many ways of representing the amount of information produced by this particular situation. In one view the amount of information is 8, as there are 8 employees - 8 possibilities. Another view is to state that the amount of information is 7, since 7 possible outcomes have obviously been eliminated. Weaver specifies a more convenient method of measuring information. In so doing the usual application of binary is extended. Binary decisions lend themselves very well to the summation of information.

Suppose (adapting Drekste's approach) that the nurses agree to make the selection based on successive flips of a coin. The choice of the single employee might then take the route depicted below. The group divides into two groups of four and the coin is tossed. The losers, Jim's group then flip the coin again, the loser once more is Jim. He has no luck even on the third and final flip.

In this instance the number of tosses of the coin can be used to represent the number of choices, or decisions made. To get from eight to the selected employee, there are three binary decisions. Each one selected from a choice of two (equally probable: The coin was a fair one!) competing alternatives. But this still does not make explicit how information can be measured? Shannon and Weaver provide a formulae for calculating the amount of information arising from the reduction of n possibilities to 1.

Drekste represents this as: I(s) = LOG n where: I(s) = the amount of information associated or generated by s; and log = the logarithm to the base 2. Thus, if there are eight (equally possible) outcomes then the amount of information associated with the selection of one would be 3 as 23 = 8 (2 x 2 x 2 = 8 or had there been sixteen possible outcomes 24 = 16 since 2 x 2 x 2 x 2 = 16). Ibid p.7

MEANING AND INFORMATION

Weaver and Drekste, indicate that it is NOT the individual messages that are units of information. It seems many are misled, on this. It is easy to confuse the concept of information with that of meaning. The concept of information lies in the situation as a whole.

'Although information, as ordinarily understood, may be a semantic concept, this does not mean that we must assimilate it to the concept of meaning. For on the face of it, there is no reason to think that every meaningful sign must carry information or, if it does, that the information it carries must be identical to its meaning.' Ibid. p.42

Dretske gives the example of a bridge tournament. He was asked what his partner's bid meant. The meaning of all bids must be revealed to opponents. But, having revealed the meaning of the bid, the opponent pursued the point: "I know what it means. What I want to know is what his bid told you, what information you got from it?" The rules do not require Dretske to reveal this particular detail. Not surprising really, since the rationale behind many games would be negated if players had to reveal their true strategies. Dretske points out: 'What one learns, or can learn, from a signal (event, condition or state of affairs), and hence the information carried by that signal, depends in part on what one already knows about the alternative possibilities.' Ibid. p.43

This also explains why we seek to adopt a non-judgemental attitude and demeanour towards patients or clients. There is a sense that all behaviour is significant, even negative behaviours. If traits are automatically attributed and judgements made based on information from a third party, without forming our own opinion, an opportunity to learn may be missed. More importantly the patient may fail to learn, in addition to the nurse.

PHYSICS AND INFORMATION

Shannon's theory has helped telecommunications to progress to its present state. To say that information is pervasive becomes crystal clear in von Baeyer's (2001) account of the application of 'information' in physics formulated by Zeilinger (1999). Zeilinger's adoption of information could be far reaching, a possibility forseen by Wheeler.

'About a decade ago, John Archibald Wheeler urged that information should take center stage. What we call reality, he thinks, arises from the questions we ask about it and responses we receive.

"Tomorrow, we will have learned to understand and express all of physics in the language of information," he said.' von Baeyer's (2001) p.28

Zeilinger makes use of this same principle.

'Zeilinger's conceptual leap is to associate bits with the building blocks of the material world. In quantum mechanics, these building blocks are called elementary systems, and the archtypal elementary system is the spin of an electron. The only possible outcomes of measuring an electron's spin are "up" and "down". You can choose any axis to measure the spin along - vertical, horizontal or tilted - but once that axis is chosen only the two results are possible, as if the electron were a spinning top that can be one way or the other, but can't point to any intermediate direction. These outcomes could just as well be labelled "yes" and "no", or, in the fashion of digital computers, "1" and "0". von Baeyer's (2001) p.28

"Zeilinger avoids the question "What is an elementary system?" and asks instead, "What can be said about an elementary system?" His conclusion is simply stated: an elementary system carries one bit of information.'

von Baeyer (2001) describes how Zeilinger's principle can lead to three cornerstones of quantum mechanics:

1. quantisation
2. uncertainty
3. entanglement. von Baeyer (2001) p.29

Minkel (2002) explains efforts to conjoin physics and information via what is called the holographic principle. This debate however has little significance for the majority of health care professionals, but why is information so undoubtedly important to them? Why do we sometimes waste vast amounts of money trying to improve our information management? The remainder of this section of the HCM website and immediate links considers this question and the issues raised.

© Peter Jones 2000

References

Bawden, D. (1992) What kind of resource is information? Computer Bulletin, Series IV,4,2,6-7.

Devlin, K. (1991) Logic and Information, Cambridge, CUP,18

Drekste, F.I. (1981) Knowledge & the Flow of Information, Basil Blackwell Publisher, Oxford

Editorial (1985) The Computer Journal, Cambridge, 28,3

Minkel, J.R. (2002) The Hollow Universe, New Scientist,174,2340,23-26.

Plato (1997 - edition) Thaetetus, Penguin.

Scarrott, G.G. (1989) The Nature of Information, The Computer Journal of The British Computer Society, Cambridge University Press, 32,3,262-266

Shannon, C.E., Weaver, W. (1949) The Mathematical Theory of Communication, University of Illinois Press, London, 8-9.

Stamper, R.K. (1985) Information: Mystical Fluid or a Subject for Scientific Enquiry, The Computer Journal, CUP,28:3,195-199.

von Baeyer, H.C. (2001) In the beginning was the bit, New Scientist, 169,2278,26-30.

Zeilinger, A. (1999) A Foundational Principle for Quantum Mechanics, Foundations of Physics, 29,631.

© Peter Jones 2000

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