[GRASS-dev] Heading towards unified dataset

[Vaclav Petras]

To better coordinate creation of the new sample dataset, I created a page
on GRASS Trac wiki:

http://trac.osgeo.org/grass/wiki/SampleDataset

I invite all to join the effort.

Please see also the discussions about the sample spatio-temporal data:

http://lists.osgeo.org/pipermail/grass-dev/2014-October/071114.html
http://osgeo-org.1560.x6.nabble.com/sample-vector-temporal-data-td5166407.html
http://comments.gmane.org/gmane.comp.gis.grass.devel/60441

http://lists.osgeo.org/pipermail/grass-dev/2014-May/068601.html
http://osgeo-org.1560.x6.nabble.com/sample-dataset-for-temporal-data-td5137870.html

On Tue, Sep 30, 2014 at 2:18 PM, Vaclav Petras <wenzeslaus at gmail.com> wrote:

> Hi,
>
> at FOSS4G we were talking about the need of unified dataset, a GRASS
> location in our GRASS case, to enable easy writing of examples and also
> tests.
>
> The location would have maps with unified names such as "elevation" and
> these names can be used in the examples and tests so that both examples and
> tests can, to certain extent, work in different locations. For examples in
> manual pages or other educational material, this would mean that it could
> be used better across more countries or areas. For tests, this would mean
> that different projection or data can be tested with the algorithms.
>
> This has of course its limits, for example the result of statistical
> analysis would be different in different locations but the point is that
> the analysis can be done.
>
> We already have NC (full) location and NC basic location. They have these
> raster maps in common:
>
> elevation
> elevation_shade
> lakes
>
> These maps are in NC basic:
>
> basins
> geology
> landuse
> soils
>
> But in full NC they have different names:
>
> basin_50K
> geology_30m
> landuse96_28m
> soilsID
>
> Of course the longer names have their reasoning in differences with
> similar raster maps in the same location but I would say that having
> unified names is more advantageous for teaching/test datasets then absolute
> clearness of names. This should be in metadata anyway.
>
> One can also argue about the unified names themselves (e.g. elevation vs
> dtm or usage of underscore) but most of it is pretty clear since it has to
> be the most general names possible.
>
> The names must be obviously in English. If somebody would like to have
> data in different language, derived dataset must be created. Perhaps it
> would be possible to provide some batch version of g.rename (but there are
> also attribute columns and others).
>
> The last issue might be what if there is nothing in the area which can be
> part of the map or if dam or pond are lakes. But we can allow for some
> inaccuracies when creating a training dataset.
>
> The other locations which can be unified are Piemonte and Spearfish.
>
> So, what are the next steps? Decide about which maps to include and which
> names to use? Let's start from the NC basic location.
>
> Raster maps
>
> basins
> elevation
> elevation_shade
> geology
> lakes
> landuse
> soils
>
> I'm not sure if geology and soils would be available in other locations,
> so we could leave out them. However, they are available for Spearfish and
> maybe for Piemonte (my Italian is not really usable).
>
> Vector maps
>
> boundary_region
> boundary_state
> census
> elev_points
> firestations
> geology
> geonames
> hospitals
> points_of_interest
> railroads
> roadsmajor
> schools
> streams
> streets
> zipcodes
>
> We would need to have at at least one map for each type. I'm not sure what
> are the crucial ones and broadly available but it seems that training
> datasets are usually near some civilization, so roads or schools might be
> available. Buildings would be nice to have.
>
> Attribute data, time series and 3D rasters and (real) 3D vectors are of
> course whole new level. So, I would start with rasters and (mostly 2D)
> vectors.
>
> Vaclav
>
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