Aspects which influence Information Quality
Recognising my naivety, I investigated requirements necessary to ensure the quality of deductions.
A search for guidance, on Information Quality, on the internet produced the following:
Wikipedia. ( http://en.wikipedia.org/wiki/Information_quality)
Justia Virtual Chase (http://virtualchase.justia.com/sites/virtualchase.justia.com/files/checklist-0.jpg)
-Scope of Coverage: the extent to which a source explores a topic.
-Authority: the expertise or recognized official status of a source.
-Objectivity:the bias or opinion expressed when a writer interprets facts.
-Accuracy:information that is factually irrefutable and complete.
-Timeliness:information that is current at the time of publication.
Neither of these sources seem to give any guidance as to how the information itself can be determined credible, reliance being placed upon the authority and possible bias of the source with no real requirement that the information should be verified.
Accuracy of Communication
A further complication is that the potential user of the information could well be less knowledgeable than the supplier, or even that the supplier does not understand the potential use. Thus, it may be that the less knowledgeable user may have to develop this feeling of credibility in a particular portion of information. This is probably defines the relationship of an engineer in industry when liaising with a researcher at a university.
This is supported in a blog by Harry Neufield (http://henrysthreads.com/2007/03/accuracy-in-communication/ ) which discussed accuracy in communication. A subscriber recommended:
“Communicative Accuracy,” by Warren Weaver (Science 7 March 1958, Volume 127). This discusses the fact that:
'the effective accuracy of a written statement depends primarily upon the interpretation given to it by the reader.
A statement may be said to have communicative accuracy...if it fulfils two conditions.
First, taking into account what the audience does and does not already know, it must take the audience closer to correct understanding.....
Second, its inaccuracies...must not mislead, must not...block subsequent and further progress toward the truth.'
These quotes describe a concern; but not a solution.
However, it does support the contention that care must be taken with the source information when making deductions.
Umberto Eco complicates things a little by saying in the Name of the Rose (p316):
' Books are not made to be believed, but to be subjected to inquiry. When we consider a book we mustn't ask ourselves what it says but what it means, a precept that the commentators of the (holy) book had clearly in mind'
This sentiment is no doubt very applicable in the case of early writings. This is not restricted to early writings, nor to negativity, since Peter Drucker admitted that he often 'made up' data to illustrate an argument.
Obviously bias is involved but I would prefer to assume that there was no intent to write untruths merely that not all aspects were covered.
As an example, Exeter Cathedral is extremely fortunate to have the Fabric Rolls; however, care is needed in order to fully appreciate their significance. The fabric rolls were the records created, by cathedral officials, to record expenditure on the fabric of the church. That is, they are written by 'medieval accountants' who were primarily interested in the financial aspects and not necessarily au fait with the technical information.
This is summarised by Salzman (Salzman; Building in England down to 1540, Sandpiper Books,1997):
'the clerks who wrote these documents were not only, like all men, liable to make slips of the pen, but often they were putting onto parchment purely logical technical terms of which they could at best give a phonetic rendering, when they did not complicate matters by attempting to latinise them.'
The implication is that the cost data, presented in the accounts, must be considered to be more credible than those of a technical nature, such as the descriptions of the work. Today, this is certainly a cause of confusion between project management and engineering,
Science advances by refuting an assumed hypothesis and so, since affirmation is not possible, it can never be considered proven. Similarly, scientific fact does not exist, merely hypotheses which have not been dis-proven.
The tendency is to consider that anecdotal evidence is irrelevant in the face of scientifically acquired (objective) data.
Anecdotal evidence is usually based upon events remembered. This is an issue
- memory is not 100% accurate
- you remember what you think is important,
- it is continually being reshaped by later experiences and attitudes,
- different people remember the same event in different ways,
- memory is selective.
There are two implications:
-Anecdotal evidence should, usually, be the precursor of the collection of (objective) data. An anecdote is not valid data but is a form of information, encouraging an hypothesis.
-Objective data can prove an hypothesis untrue whereas an anecdote cannot. However, the data must be verified before it can be considered useful.
Simplistically then, valid evidence can be considered as a combination of anecdotal and verified (objective) data.
Against this, a supposition (http://www.socialresearchmethods.net/kb/dedind.php) is an assumption and, therefore, risks being more creative than factual.
Reality can be flippantly defined as that which, 'when you stop believing in it, doesn't go away'. (Philip K. Dick; "How to Build a Universe That Doesn't Fall Apart Two Days Later", 1978 US science fiction author (1928 - 1982)) .
Convictions seem to be often based upon belief rather than reality.
Coincidence is the occurrence of an event in conjunction with another event. As such, a coincidence occurs when something unexpected happens but not under a defined relationship.
Much of my work on Reverse Engineering seems to be based upon coincidences and it does appear that there is a point where coincidences complement each other.
Whilst this appears to create a semblance of credibility, it does not constitute proof.
In 'The Grand Design' (Hawkins and Mlodninov; 'The Grand Design'), the 'form' of a typical hypothesis, as defined through the use of a model, is discussed in order to describe, define and predict events. The properties of a good model are listed as:
- It is elegant,
- It contains few arbitrary or adjustable elements,
- It agrees with and explains all existing observations,
- It makes detailed predictions about future observations that can disprove or falsify the model if not borne out.
The approach becomes almost experimentally scientific, coming down to documenting a series of hypotheses and continuing the development in a controlled manner such that the current cathedral is developed, or the series of hypotheses is disproved.