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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=19820It 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/omIn 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
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