Pat Hayes wrote:
>>
>> Like functions that are non-computable, the "true" value of a physical
>> quantity
>> is non-measurable and therefore not knowable.
>
> Even if true, this is irrelevant to ontology engineering. Ontology is
> not epistemics. The ontology does not set out to describe what can be
> known. It sets out to describe the reality described by the knowledge.
> Unless you want to argue that because we cannot know a true value, that
> therefore no true value exists - a coherent point of view, but not one
> conducive to communication or normal conceptual description - then
> please don't put scare quotes around 'true' (01)
I take a third way: I am agnostic on 'true' values.
Why do we need such an hypothesis, anyway?
We have known, measured values, which are less likely to be fictitious, and
they
have uncertainty. (02)
In a model, any numerical value you bind to the quantity, Q, that suggests that
that value is the unique, true value of the object in physical reality that Q
refers to, is a lie. You can only bind a received value to Q, and those values
are ultimately received through some form of measurement process. (03)
I'm still not sure there's a consensus on requirements for a UoM effort.
Nevertheless, I'm not saying we need to be able to capture all of what is
knowable. I am just saying that we should be able to capture at least what is
actually known. I count among actual knowledge our past & current sense
perceptions, measurement data, and pure mathematics.
The grander sense of reality you refer to (grander meaning large, comprehensive
and consistent) is achieved by synthetically applying abstraction (mathematics)
to create models that are consistent with our actual knowledge. (04)
You suggest that the purpose of UoM is to "describe the reality described by
the
knowledge", but do you not think it as important, if not more important, to
describe the knowledge itself? It seems you are saying that the model we create
has more importance than the knowledge that proves the validity of the model. (05)
I believe it is antithetical to a scientific perspective to accord more
importance to any single model of reality than to our measurement data upon
which the models rest. (06)
> Electrons do have a true
> rest mass, even if we can only measure it to a certain precision. (07)
This notion of a true electron rest mass is not supported by the evidence. It
is
unique to the degree that it can be reliably be measured and give the same
value
repeatedly (to within measurement error). (08)
Earlier on this reflector the case of the problematic concept of "boiling
temperature of water" was pointed out. You may have a nice model/theory of
phase
transitions, but since a (unique) boiling temperature can be difficult to
measure, reality shows itself to be messier than the model. We cannot just
assert in the face of the evidence that there is a true boiling temperature. We
cannot predict when evidence contrary to any expectations we hold will arise as
we refine our measurement processes, not even for an electron's mass. The
quantum theory holds that there is an essential uncertainty in the concept, not
just a measurement uncertainty. (09)
> We still however assume that they exist, and our science and engineering
> and trade rules and laws and our ordinary communication all are based on
> this presumption. So our ontologies should speak of these things that we
> all assume to exist. (010)
I don't see how they are based on the hypothesis of 'true' values.
They are based on values measured against defined standards, the essence of the
SI & VIM. (011)
Some people understand the Fahrenheit and Celsius temperature scales to be
based
upon the melting and boiling points of water. That may have been true in the
past, but they are currently defined in terms of the more precisely and
reliably
measured triple-point of water (referenced to absolute zero). One reason, I
presume, is that the boiling point failed to be a true, consistently measurable
value. The choice of standards for units are largely predicated on the degree
of
precision to which we can measure certain quantities. The standards are subject
to being changed when we can improve our overall precision in measuring those
quantities by different methods and different defined quantities. It is, for
example, expected that the standard for mass will soon change. (012)
Trade rules and laws, when sensible, defer to scientific, engineering, and
mathematical knowledge (and don't, for example, legislate the value of pi or
the
nature of reality). (013)
>>
>> I think the more important questions are "Must it be done?" and "Can
>> it be
>> done?" rather than "How long will it take?".
>>
>> My answers are "Yes", "Probably", and "I don't know", respectively
>
> and mine are: no, not in the near future, and God alone knows, but
> people have been trying for several decades and havn't got very far. (014)
If God alone can have an idea of when a computational model of a fairly
well-defined representation of uncertainty can be achieved, how can any mortal
ever hope to make progress on the ontology engineering task to "describe the
reality described by the knowledge". (015)
To me, the latter sounds ill-defined, far more complex, hence enormously more
difficult. (016)
>>> Yes, in the abstract, 'uncertainty' is well-defined. It is the
>>> expression of
>>> uncertainty that is interesting. Presumably we would include the
>>> concept so
>>> that uncertainties can be expressed. Would you be happy with a
>>> 'quantity-value has-uncertainty simple-quantity-value' property (with
>>> the
>>> basic SI definition = the maximum amount by which 'quantity-value'
>>> may differ
>>> from the actual value)? What about conditions, e.g. "at standard
>>> temperature
>>> and pressure"?
>>
>> So, when is something completely unambiguous? Almost never.
>
> ? Why are you talking about ambiguity? That is yet another distinct
> topic (apart from probability and tolerance). (017)
If I specify a quantity as "4.0 newton meters", some may say that is an
ambiguous quantity, since I have not specified the Kind, e.g., torque or energy.
I say it is also ambiguous if you do not interpret or specify an uncertainty,
for example, if "4.0" is not interpreted as the interval [3.95, 4.05] (SI
standard practice interprets the interval). This raises (in my mind) the
question, how much more do I need to specify to be unambiguous? I believe the
answer is subjective, or based on requirements.
My answer (currently) in order of importance is
(nominal numerical value, coherent derived unit value, uncertainty value,
derived quantity value, . . .) (018)
>> How much qualification is enough? As much as it takes for the user to
>> be happy.
>> Does the user always specify what it takes to make him happy? No.
>> I think that an expression of uncertainty is a first level of
>> qualification. (019)
>> So, my wife hands me a grocery list. It says "milk, bread, eggs".
>
> OK, already this example is irrelevant. Your problem here is
> interpreting natural-language in a social context. This is about as far
> as it is possible to get from anything to to with ontology engineering. (020)
This is meant to be a hypothetical use case.
Please ignore any social-context or natural language issues. The context is
meant to demonstrate that uncertainty is an everyday concern, even if it is not
explicitly expressed.
It is also meant to illustrate how resistant users can be in providing
unambiguous specifications of what they want. In this case, even the nominal
numerical value is unspecified. (021)
Assume, instead, you are engineering an agent to fulfill a grocery order. What
does agent need to 'know' to satisfactorily fulfill the request? What is an
unambiguous specification? (022)
R/jbc (023)
>
>> Suffice it to
>> say that my wife is not easily trained to my expectations: she never
>> specifies
>> amounts, let alone a range of acceptable quantities. I do like to keep
>> her
>> happy, though, and, as important, I don't want to have to repeat the
>> shopping
>> trip daily.
>> I have learned that, having 3 kids, a quart of milk is insufficient,
>> and ten
>> gallons is excessive. I've even narrowed it down better than that.
>> Perhaps she
>> has trained me to her expectations.
>>
>> I am happy to report, however, that, even after untold man-years of
>> effort,
>> computers are dumber than I am (stay tuned?).
>> I'm pretty sure that if computers are ever able to deliver on such a
>> request,
>> then to keep my wife happy they will have to have a rudimentary
>> capability to
>> process uncertainty. Until they can, I still am useful. Perhaps I am
>> trying to
>> put myself out of a job?
--
_______________________________
Joseph B. Collins, Ph.D.
Code 5583, Adv. Info. Tech.
Naval Research Laboratory
Washington, DC 20375
(202) 404-7041
(202) 767-1122 (fax)
B34, R221C
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