Overview of IDQ Deficiencies Which Are Evident In Scripture

The originators of scripture had a remarkable lack of insight when creating scripture considering it was revealed to them by God. Apparently God didn't reveal to them some fundamental principles in ensuring they were creating quality information and data that would stand the test of time and generations.

This article introduces Information and Data Quality design deficiencies which will be elaborated on with scriptural examples in follow on articles and will serve as quick reference for them. It is part four of a series on applying IDQ priniciples to cross-checking the authority and trustworthiness of the Bible. Links to the preceding articles follow.
1. How Accurate is the Bible?
2. Applying Data and Information Quality Principles To The Bible
3. Applying IDQ Principles of Research To The Bible

What are Design Deficiencies?
As the saying goes "Do it right the first time" many industries recognize and practice the principle of ensuring quality early in the production cycle to avoid problems later in the cycle or in the market(27). As a marksman knows when taking aim, a tiny deviation from the target at the source can lead to large deviation at the target. By not ensuring data integrity and quality at the creation of scripture, many problems have manifested themselves and continue to appear as the scripture gets older. Metaphors do not retain their integrity in meaning over thousands of years. Some of the problems have led to persecution for heresy, divisions in the church and division of the Churches into denomintations until there are tens of thousands of variations of Christianity in existence. For example, they may all agree that Jesus died on the Cross, but they don’t all agree on his nature.

With these kinds of problems it is no wonder why after close to 2000 years, Christianity has only a 33% mind share while all other religions together total 66%(28). Its not that people are evil so they don't believe, it is that there are no compelling reasons to believe in Jesus. Comparing all these religions to some other philosophical ideas that were developing in parallel about the same time, Mathematics has become ubiquitous while the various religions are still languishing under the weight of implausibility(26).

The originators of scripture had a remarkable lack of insight when creating scripture considering it was revealed to them by God. Apparently God didn't reveal to them some fundamental principles in ensuring they were creating quality information and data that would stand the test of time and generations. And furthermore God had a choice in who he revealed scripture to. Using the law of large numbers, he would have been able to analyze and consider any number of millions of starting points for his desired outcome to include the one person that would start a path of reliable transmission of the data from person to person(29). He, like no one else, had the ability to choose the one in ten million starting point that would have gotten the scripture to this point uncorrupted.

Overview of Proper Representation and Design Deficiencies
Some fundamental deficiencies in data design and creation have been identified in the field of Information and Data Quality through research and trial and error(3). Each of them will be defined in this overview and then how they relate to scripture will be elaborated on separately in follow on articles.
They are as follows.
- Incomplete representation
- Ambiguous representation
- Meaningless representation
- Garbling by mapping to a meaningless state
- Garbling by mapping to a wrong state

Proper representation
In order for an Information System (IS) to accurately represent real world events, each of the datum in the Information System must "map" to real world states. Each real word state must be accounted for in the information system. Having more than one instance of a Real World state (a record) is appropriate if it represents an aspect of the Real World state that hasn't been previously accounted for. To have more than one instance of a record of the same Real World state doesn't add any significant value, but a record of the same Real World state that has related data, in another context for example, adds value if it doesn't lead to a meaningless Real World state such as a contradiction. For example, having two instances of the same story do not add any value unless one of the stories has different information in it which does not contradict the other. Figure 1 illustrates this point by showing three instances of data represented by spheres in the column labeled RW (Real World) and four instances of Data in the D column. Each Real World state is represented by a datum in the information system with one instance of a Real World state being represented by two instances of data in the Information System.

Figure 1.


Incomplete representation
If the Information System is missing some information about the real world, then the information system cannot accurately represent the state of the real world for which it was intended. This is termed as "incompleteness". Figure 2 illustrates this point by showing three instances of data represented by spheres in the column labeled RW (Real World) and two instances of Data in the D column. One instance of a Real World state is not represented by the Data in column D.

Figure 2



Ambiguous representation
While it is permissible to use to a multiple datum to represent one real world state, it is not permissible to use one datum to represent two real world states. If multiple Real World states are represented by one datum there is not enough information with which to accurately represent either Real World state. This situation is called "Ambiguity". It is similar to incomplete representation because it can be considered an instance of missing information, even though one datum could incompletely represent two instances of a Real World state because it is not specific enough. It is analogous to using the term "she" in a conversation when discussing an event concerning multiple women. By not specifying which "she" is being referenced, the details of the event become unclear because the "she" being referred to is ambiguous.

Figure 3 illustrates this point by showing three instances of data represented by spheres in the column labeled RW (Real World) and two instances of Data in the D column. One instance of a Real World state is not represented by the Data in column D but instead, two instances of Real World states are represented by one instance of an information state.

Figure 3



Meaningless representation
When the information system contains superfluous information then it can lead to a situation where the Information System does not accurately represent (map back to) a real world state. For example this can occur by the use of too many descriptive terms, undefined terms or some minor addition to the story intended as an elaboration. To say that in a battle some person or group chose a brilliant strategy and exhibited exceptional strength or bravery may mean that an unintended desperate situation has been incorrectly represented and will be incorrectly interpreted. This situation happens often in television, movies and songs about historical events such as the Spartan battle with the Persians at Thermopylae depicted in the movie "300" or Egyptian Hieroglyphs documenting events in the lives of pharoahs.

Figure 4 illustrates this point by showing two instances of data represented by spheres in the column labeled RW (Real World) and three instances of Data in the D column. One instance of an information state is not represented by or does not map back to a real world state .

Figure 4



Operation Deficiencies - Garbling:
Meaningless State
In human terms, garbling occurs at the point of "consumption" or reading and interpretation. In Information Systems, it occurs at operation time or when the database is being accessed. Garbling occurs when a Real World state is incorrectly mapped to a wrong state in the Information System. There are two cases in which this occurs. If a meaningless state exists, then Real World mapping will be to a meaningless state, or the mapping might be to a meaningful but incorrect information state. This can occur as a result of inaccurate data entry or omissions of real world states at the creation or origin of the data. Analogous examples of this type of garbling are legends, folktales and the "Artistic License" of the author or originator.

Figure 5 illustrates this point by showing two instances of data represented by spheres in the column labeled RW (Real World) and three instances of Data in the D column. One instance of an information state is not represented by or does not map back to a real world state and a Real World state in incorrectly interpreted as being represented by the superfluous datum.

Figure 5



Map to a wrong state
Figure 6 illustrates this phenomena by showing two instances of data represented by spheres in the column labeled RW (Real World) and three instances of Data in the D column. One instance of an information state is not represented by or does not map back to a real world state and a Real World state in incorrectly interpreted as being represented by a valid however incorrect or unintended information state.

Figure 6


In successive articles I will explore each IDQ design deficiency and give a biblical example.

REFERENCES AND FURTHER READING
1. Wikipedia, "Data Management"
2. Information Quality at MIT
3. Anchoring Data Quality Dimensions in Ontological Foundations
4. DMReview, Data Management Review
5. IQ-1 Certificate Program
6. Wikipedia, 2003 Invasion of Iraq
7. How Accurate Is The Bible?
8. Datalever.com
9. Wikipedia, Tanakh
10. Null Hypothesis
11. Beyond Accuracy: What Data Quality Means To Consumers
12. IQ Benchmarks
13. Reasonable Doubt About Adaption Theory
14. IQ Trainwrecks
15. Robert Harris' VirtualSalt
16. Data Quality Assessment
17. Cornell University Library
18. Guidelines for Ensuring and Maximizing the Quality, Objectivity, Utility and Integrity of Information Disseminated by Federal Agnecies
19. East Tennesee State University Researchers Toolbox
20. George Mason Univeristy
21. McGraw-Hill Higher Education, Evaluating Internet Resources
22. The Virtual Chase, Criteria for Quality in Information--Checklist
23. Know Your Bible
24. Wikipedia, Authors of The Bible
25. Ancient HistoriansPart 1, Part 2
26. Wikipedia, History of Mathematics
27. Data Quality Requirements Analysis and Modeling
28. Major Religions of the World Ranked by Number of Adherents
29. Making Sense of Probability

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