Roy again asked for some use cases for UCD's so here is my favorite.
I need accurate distances to nearby galaxies. So, I am very picky as
to the kind of distance estimate. E.G., a distance derived from a
redshift will not do for nearby galaxies. So I can't just query on
phys:distance, there must be a simple way to distinguish the distance
quantity by method used to obtain the distance. And to look through
every paper on distances of galaxies, one by one, would take months.
Most desireable methods:
Period-Luminosity Relation of Cepheid variables
ditto for RR-Lyrae variables
CCD-based IR-Tully-Fisher Relation (rotation velocity vs. IR
Magnitude)
Tip of the Red Giant Branch (brightest TRGB stars)
Supergiant Stars atomic hydrogen Equivalent widths vs stellar mag
spectroscopic eclipsing binaries (none published yet)
Maser orbits
Type Ia Supernovae Peak Brightness
Surface Brightness Fluctuations
Less desired (>20% error):
Redshift using Hubble relation or some other flow model
Brightest Stars
B-band Tully-Fisher Relation
IR-Tully-Fisher with single aperture IR magnitudes
Dn-Sigma (alias: Faber-Jackson Relation) (central size vs velocity
displersion)
Expanding Photosphere (Baade-Wasselink Method)
*Supernova
*Planetary Nebula
Largest HII regions
Perhaps the simplest thing is to have error bars for all data and then
one could
simply ask for small error bar data. But distance papers are notorious
for underestimating errors. So one needs to use knowledge from
cross-studies on what the real errors on these various distance
estimators are.
Another similar example would be the temperature of a star or ISM cloud.
There are various techniques for obtaining that property, but each one
measures a substantially different statistic of T or T at various depth.
So, is this a job for UCDs? Data Model? Shouldn't standard
astronomical methods of obtaining a property be part of our controlled
vocabulary? If not in UCDs then in some other dictionary/ontology? Or
is it beyond our wildest dreams? (Well not mine, but ours.)
Ed
Received on 2003-10-23Z20:00:57