Hi Bas,
Current aggregation capabilities have been targeted at particular types
of homogeneous collections of datasets. In particular, the "Union"
aggregation would work with a collection where different parameters were
stored in different files but the dimensions of the arrays were the
same. The "JoinExisting" aggregation would work with a collection
containing all the same parameters in each dataset but the time
dimension, for instance, changed from file to file. The "JoinNew"
aggregation is similar to the "JoinExisting" but the variables wouldn't
have a time dimension, the time dimension would be specified in the
aggregation setup.
We haven't yet worked on any aggregation that would knit together
varying geographic footprints.
Here is the documentation on NcML aggregation in general, it goes into
some detail on "Union", "JoinExisting", and "JoinNew":
http://www.unidata.ucar.edu/software/netcdf/ncml/v2.2/Aggregation.html
Here is the documentation on using aggregation in the TDS:
http://motherlode.ucar.edu:8080/thredds/docs/NcML.htm
A side note:
Another possible future direction we sometimes talk about involves
collection types and the searching/subsetting of collections. Kind of
the flip side of aggregation or an alternate if aggregation seems too
hard. Basically, it would involve providing a service that knows enough
about a data collection to allow querying to retrieve the subset of the
collection that matches your query. We haven't gone down this road as
far as we have with aggregation but it might be a better fit for the
situation where the geographic footprints of dataset don't mesh together
easily.
Sorry none of this directly addresses your issue.
I'm going to CC one of the IDV guys and see if they have any thoughts on
this.
Ethan
Bas Retsios wrote:
Hello Ethan,
It has been a while since our last communication (mainly due to the
fact that it is holiday season).
I have made some improvements in CrawlableDatasetDods, to make it
compatible with a few more DODS servers. When it is mature enough, I
will submit it to you.
Meanwhile I am still learning what can be done with the catalog.xml
files in the current Thredds version (3.10), because our original
objective was to make the querying of MODIS images easier through
Thredds.
I would like to ask some clarification for one of the aspects of
Thredds, namely aggregation.
Check the following datasetScan section:
<datasetScan name="DodsTest2" path="MOD021KM.005"
location="http://g0dup05u.ecs.nasa.gov/opendap-bin/nph-dods/OPENDAP_DP/short_term/MOGT/MOD021KM.005";
ID="nasaTest2" addDatasetSize="true" addLatest="true">
<crawlableDatasetImpl
className="thredds.crawlabledataset.CrawlableDatasetDods" />
<metadata inherited="true">
<serviceName>remoteopendap2</serviceName>
</metadata>
</datasetScan>
This gives me a huge list of satellite images. Each image covers a
different location on earth.
Is there a way to use the Thredds "aggregation" functionality in order
to get one huge virtual image covering the entire earth? If yes, what
elements should I add to my catalog.xml? (I found options
datasetAggregation and netcdf\aggregation). Is there an example I can
look at?
My purpose is to use IDV as a client on those images. The current
behaviour (with the datasetScan above) is that IDV lists the images in
the dataset, and I have to make a selection based on filename, without
knowing the area covered. I would prefer indicating a bounding-box,
and let IDV load the necessary images for me.
Thanks in advance,
Bas.
--
Ethan R. Davis Telephone: (303) 497-8155
Software Engineer Fax: (303) 497-8690
UCAR Unidata Program Center E-mail: edavis@xxxxxxxx
P.O. Box 3000
Boulder, CO 80307-3000 http://www.unidata.ucar.edu/
---------------------------------------------------------------------------
