Re: Lessons (was Re: Objects and Relations)

On Feb 12, 6:27 pm, Bob Badour <bbad..._at_pei.sympatico.ca> wrote:
> Bob Badour wrote:
> > What lessons have you learned that you might want to relay? (Please
> > enumerate.)

Heck, why not. With the all-encompassing caveat that the follwoing is all off the top of my head:

1. Implementation != Theory
2. To produce good IT we should be analysing _Information_ not just Technology.
3. Value based addressing.is superior to OID's.
4. Values should never be hidden.
5. Propositions are simply true or false and do not 'change'.
6. OID's break liebniz equality.
7. Encapsulation has a negative impact on shared data, leading to query bias.
8. Query neutrality is important for good management of shared data.
9. Do not confuse conceptual/physical/logical layers.
10. Purely Navigational Databases are inferior to Declarative Databases.
11. Nulls are both nonsensical and generate logical errors.
12. There are two types of updates masquerading as one - domain redefinitions/proposition replacement,
13. RM redefines some mathematical concepts - tuple/relation/crossproduct.
14. Semi-structured data has no definition.
15. Keys are not entity identifiers, nor vice versa. Keys are the antecedents of material implication.
16. Surrogates are still attributes, just unobserved ones.
17. Combining XML with xlink and xpath to create a data model is like grafting arms and legs on to a hamburger.

>
> 1. The self-proclaimed seldom are.
> 2. Not every human mind is equally able.
> 3. Intellectual honesty is a prerequisite to learning.
> 4. Not every human mind is capable of abstraction.
> 5. Some non-human minds are capable of experimentation and methodology.
> 6. Success is context-sensitive.
> 7. Our tools affect our minds.
> 8. The predicate calculus is more illuminating than the set algebra.
> 9. Programmers are drawn more to the algebra than the calculus.
> 10. Theoretically non-updatable views should nevertheless be updatable.
> 11. It is very difficult to respond coherently to that which is incoherent.
> 12. Good intentions can lead to disaster.
> 13. Selfish motives can lead to great good.
> 14. Continuous assessment and improvement are best.
> 15. Empiricism is the only hope to understand reality.
> 16. Caution is appropriate when designing.
> 17. Wanton recklessness is appropriate when imagining.
> 18. The scientific method keeps natural human deficiencies in check.
> 19. We should strive to tackle problems at or near the limit of our
> capability.
> 20. Austere mental discipline is required for real progress.
> 21. A pleasant demeanor can make nastiness palatable.
> 22. An unpleasant demeanor can unmask intellectual dishonesty.
> 23. Some with an unpleasant demeanor are simply nasty.
> 24. There is no stopping the invincibly ignorant.
> 25. Humans tend toward irrational and non-rational belief.
> 26. Status hierarchies are very important to human happiness.
>
> > What audiences do you try to reach with these lessons?

1. Those who are making the same mistakes I encountered
2. Students
3. Colleagues

>
> 1. Family
> 2. Friends
> 3. The readers of c.d.t
>
> > What approaches have you used?
>
> 1. Profanity
> 2. Intimidation
> 3. Disdain
> 4. Understatement
> 5. Overstatement
> 6. Provocation
> 7. Asking questions
> 8. Absense
> 9. Sophistry
> 10. Referral to better sources
> 11. Self study
> 12. Appeal to reason
> 13. Logic
>
> > What other approaches are you aware of?
>
> 1. Absolute empiricism with quiet skepticism
>
> > What other audiences might exist?
>
> 1. Colleagues
> 2. Students
> 3. Web surfers
> 4. Other programmers and data managers
> 5. Other types of professionals
> 6. Executives
> 7. Academics
> 8. Random strangers
>
> > What big questions remain unanswered in your mind?

1. Is a fully relational language tractable.
2. Is it possible to generalize Codd's insights without relations.
3. Is an MV system (ignoring current suggestions and implementations) ever justifiable.
4. View updatability.
5. Is it a valid approach to consider a stuctural layer between logical and physical.
6. Is it possible to provide a mechanism to prevent the same mistakes continually occurring in IT.

>
> 1. What are the biggest challenges to distributed optimization?
> 2. Where will the next great insights lead us?
> 3. How will germline genetic engineering affect our offspring?
> 4. How long will it take to achieve engineered negligible senescence?
> 5. Where can I best devote my effort?
>
> > How do you measure success?
>
> 1. When I gain an insight
> 2. When I communicate an insight
> 3. When someone exceeds my expectations
> 4. When I see something admirable
> 5. When I improve an efficiency
> 6. When I remove a systemic defect
> 7. When it compiles
> 8. When it behaves as expected in the debugger
> 9. When it runs
> 10. When my dogs run and play
> 11. When I increase my serenity

1. Insight
2. Elegance
3. Serenity