Ben's clarification from O&M also helps minimize or avoid a possibly
approaching train wreck. The initial definition was feature: just a geographic
thing the next definition was feature: abstraction of real-world phenomena (so it
is no longer the physical thing, just the abstraction), and the discussion after
that suggested to me feature: a digital artifact, possibly with associated digital
services and attributes.
Since in many standards the term 'feature' or similar is (arguably) referring
to the thing being observed, and is referenced by a URI that names that
physical entity, it will be helpful to keep the following concepts distinct:
a) the real-world entity (this would be something wet, for example)
b) a URI-style or other computationally usable reference to that real-world
entity (this is just an identifier), and
c) an abstraction of this (or any) real-world entity that lives in a model
or computer program and describes the entity
Things like points, lines, areas, and volumes seem to be solidly in the third
category. Features of interest seem solidly in the first category, until you
have to refer to them with a 'name', then the name itself is in the second
category. (There is a long list of possible definitions of the term in the
Oceans IE report submitted to OGC, 08-124 if you have access; list is appended
below). Coverages and sampling features also are of the third class, though
possibly containing reference to an actual entity by location or name.
I apologize if I didn't get those divisions exactly right, but I'm sure at
least these 3 concepts usefully co-exist.
john
List of things a feature could be:
- earth realm (ocean, river)
- medium (air, water)
- location
- event (Hurricane Katrina)
- system (given platform)
- named region
- shape made by a procedure (path of a glider) For that evaluation we went
with 'earth realm'.
On Oct 7, 2008, at 11:07 AM, Ben Domenico wrote:
Hi Jon,
Feature/coverage is a distinction I've struggled with for some
time. George has pointed to one of the documents that I have found
most helpful in terms of a general conceptual definition of a
coverage -- the ISO 19123 document which is also an OGC spec as
George points out.
http://portal.opengeospatial.org/files/?artifact_id=19820
It defines things from a mathematical point of view in terms of
what I used to think of as the independent variables (domain) and
dependent variables (range). One area where ISO 19123 is a bit weak
from the metoceans perspective is that it has a limited view of
"continuous" coverages. Where metoceans models the continuous
function space in terms of the equations of fluid dynamics, ISO
19123 does so in terms of strictly geometric equations.
Nevertheless the defining concepts are very valuable and the
discrete coverage concepts map well into our metoceans data
collections.
Others may disagree with me on this, but the other documents I find
helpful in understanding these feature/coverage concepts are those
of OGC Observations and Measurements.
http://www.opengeospatial.org/standards/om
In particular they define "features of interest," examples of which
might be the Indian Ocean or the atmosphere above London. This sort
of feature fits will into metoceans community which models such
entities in terms of functions governed by the equations of fluid
dynamics. Moreover, many of our observational data collections and
forecast model outputs are really just samplings of the value of
those functions at discrete points in space and time. O & M uses
the concept of "sampling features" for that sort of dataset. For me
the sampling feature is very helpful for developing an understanding
from the user point of view. The sampling features are generally
categorized by dimensionality: point (a station observation), curve
(a vertical sounding), surface (satellite image), solid (forecast
model output).
One other useful element of the O & M framework is that it
explicitly deals with collections of data. For example a
collection of measurements and sounding profiles from observing
stations can itself be considered a sampling feature. And such a
collection is a sampling feature that fits into the coverage
category just as the satellite image and forecast model output do.
So such collections are considered coverages even though the
spatiotemporal points are not regularly spaced. In the case of
observing stations, the locations have to be specified in a table
rather than by an algorithm. In the case of observations from ground-
based radars, the locations are defined by a table of stations and
an algorithm describing the scanning geometry. Many of our
metoceans datasets are just such collections. But the key point is
that, in the world of ISO 19123 and OGC O & M, these data
collections are indeed coverages.
Enough for now, but these documents are relatively easy to read and
are very helpful at the conceptual level.
-- Ben
