Luc Maisonobe wrote:
Bear Giles a écrit :
Hi, I was wondering if there would be interest in numerical models of
physical constants. For instance, saturation pressure of water vapor in
air at a particular temperature. It would also be appropriate to
provide a method to get relative humidity from wet and dry bulb
temperatures since it directly relates to this saturation pressure. All
of the models should be time-invariant, e.g., no historical weather
observations.
I'm puzzled about this proposal. The scope seems completely unbounded
and will get out of hand quickly.
I would better see such a project under the wing of wikipedia or some
foundation like that.
It's not an all-or-nothing situation where the project is only usable
after thousands of models exist. Instead I would see it slowly adding
models as people 1) discover the tools and 2) scratch their own itch.
There may only be 10-20 methods added at a time, but that could be
enough to significantly enhance the project. I've worked with
meteorological models in the past so it's a natural place for me to use
as a seed.
Also, I might not have been clear earlier that I'm thinking -solely- of
curve-fitting observational data, either directly or via simple
calculations of the same. As a model, we might have observational data
like:
x,y = (0,0.9), (1,2), (2,5.1), (3,10.3)
and the resulting model is y(x) = 1 + x*x. Not quite 100%, but it's
curve-fitting instead of calculations from first principals. It would
just be policy that only the basics of general interest would be modeled.
I know [physics] is too broad, that it should be [physics-?] with ? to
be determined.
A simple unexplained model isn't very useful so there would be multiple
elements:
1) a significant and attributed dataset.
At least in France there is a real problem with data collections like
that. The law that governs intellectual property (the « code de la
propriété intellectuelle ») does have specific requirements about
database. Roughly, if someone has already established a database
containing anything, you cannot build a similar database containing only
the same data without infringing its rights.
So there's definitely a need to separately package the models and any
supporting information.
BTW I'm not sure if this is legally a database since we're talking about
collections of data that anyone could get in the lab. There's nothing
proprietary in the sense of a database containing Amazon orders for the
population of a city. It's far closer to the US Intel case where the
company successfully stopped a competitor from using "move" in their
assembler (the other company had to use something different like "mov"),
but could not stop them from having their assembler emit the proper
opcode for the instruction. The ruling was based on the idea that the
choice of the mnemonic was up to human discretion, but the opcode was
fixed and unique even if it was arbitrarily assigned by Intel during the
design phase. The competitor could not emit a different opcode and
expect the correct behavior.
To be honest I'm not 100% certain how useful the underlying data would
be, but I keep coming back to the academic question of "how do you know
this?" on the models. Most people would be happy to just have a small
java library that lets them avoid entering data by hand, but researchers
would legitimately need to know the source of the model. If we say, by
fiat, that these concerns will not be addressed then we don't need to
worry about providing the underlying material beyond a simple reference.
[math] should remain as independent to application as possible.
It would definitely be a one-way street. But there's no point in
writing a method for, e.g., Hermite polynomials if it already exists in
[math]. Obviously something general like that would be offered to
[math], but there wouldn't be any sort of assumption that it would be
accepted.
Bear
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