Re: [galeon] Fwd: CDM feature and point types docs

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Andrew.

I agree that there are geometries around which we often base our data in the
scientific community. However, perhaps what Gerry is talking about comes
from a SWE influence where we focus more on pure observations, which can
then be organized into geometries based on your needs or based on the
sampling pattern.

Perhaps the attached email from the SensorML Forum might explain this
concept better.

Thanks.
Mike Botts

--------------------------------------------------------
Mike Botts, Ph.D.                   mike.botts@xxxxxxx
Principal Research Scientist          http://vast.uah.edu
NSSTC University of Alabama in Huntsville (256) 961-7760
Huntsville, AL 35899 USA            (256) 652-0165 cell
--------------------------------------------------------

-----Original Message-----
From: galeon-bounces@xxxxxxxxxxxxxxxx
[mailto:galeon-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Woolf, A (Andrew)
Sent: Thursday, March 13, 2008 3:52 PM
To: Ron Lake; Gerry Creager; Unidata GALEON
Subject: Re: [galeon] Fwd: CDM feature and point types docs

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




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