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I should probably calm down - but: This really gets my goat! I've had rabid arguments with Rob Atkinson (& to a lesser degree Simon Cox) on this point. Actually, there's a whole community out there (actually several) whose universe of discourse is MOST DEFINITELY these kind of geometric/topologic/sampled objects. Points, profiles, trajectories, grids - this is the scientific language they use, and which defines *all the important semantics* of their data for most of the work they do. To suggest that's not what they mean is - at best - to risk alienating a very large group of potential users who already view 'GIS' with skepticism; at worst to appear patronising and arrogant. There are in fact very good reasons why such feature types *are* the kinds of things they should call feature types. Let me quote from our CSML manual: Physical processes occur in the natural world across a wide spectrum of spatial and temporal scales, and considerable science informs the design of experimental sampling strategies. It should be no surprise, conversely, that the geometry and topology of observation sets are a fundamental determinant of the scientific uses to which they may be put. Moreover, the properties of the instruments used to generate data themselves place constraints on their interpretation (e.g. as regards accuracy, precision, calibration, required post-processing, etc.). These two factors - the scientific utility of a sampling regime, and the limitations of an observing process - lead to a natural, scientifically important, classification of data types along these axes. Quite often the two are highly correlated (certain instruments generate certain samplings), and so scientific communities of practice adopt more abstract conceptual information classes that nevertheless reflect artefacts of sampling or instrument-type. This is particularly evident in the climate sciences, where broad information classes based on measurement-set geometry and topology have almost universal acceptance. The following examples are illustrative. The US National Oceanographic and Atmospheric Administration (NOAA) is developing a plan for a Global Earth Observing Integrated Data Environment (GEO-IDE) to integrate measurements, data and products and create interoperability across data management systems. In the GEO-IDE Concept of Operations (https://www.nosc.noaa.gov/dmc/docs/NOAA_GEO-IDE_CONOPS-v3-3.pdf), the following 'structural data types' are defined: Grids, Moving-sensor multidimensional fields, Time series, Profiles, Trajectories, Geospatial Framework Data, Point Data, Metadata. The ESRI 'ArcMarine' Data Model for marine data includes classes like Instant, Location Series, Time Series, Profile Line, Track, Sounding, Survey, {Ir}Regularly Interpolated Surfaces, Mesh Volume, etc. File formats such as netCDF and NASA Ames utilise data models that reflect these structures (e.g. netCDF four-dimensional gridded lat-lon-height-time variables, or NASA Ames time-series at a point). Questioning marine or atmospheric scientists about whether they really want to model their world in terms of point and other geometric feature types really risks getting some people (like me!) heat up! Regards, Andrew
-----Original Message----- From: galeon-bounces@xxxxxxxxxxxxxxxx [mailto:galeon- bounces@xxxxxxxxxxxxxxxx] On Behalf Of Ron Lake Sent: 13 March 2008 17:09 To: Gerry Creager; Unidata GALEON Subject: Re: [galeon] Fwd: CDM feature and point types docs HI Gerry: I understand, but I think it is more a question of being observations that had some property which is point valued, rather than being points first. Keiran's example is relevant as the observation could have multiple geometric characteristics associated with it. I hope I did not in any way imply you were "clueless" - not at all my intention. I think your viewpoint leads to more rigid structures for data representation and that was certainly the case in the domain of conventional planimetry. I would argue that no instrumentation can make point measurements - but that will get us into a longer and likely not so useful debate. R
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