Dear Roy,

     thanks a lot for this nice example of true interoperability. Yet, two 
questions remain: 1) what I would be even more interested in is the inverse 
problem, i.e. given a standard_name, I would like to know which compound it 
contains. 2) I expect that this is more difficult, in particular if we don't 
know a priori that the given standard_name does contain a compound name. 
Generally, this is where I see the difficulty with your brokered approach: how 
do you find out which controlled vocabulary list(s) have to be applied in order 
to identify the components of a standard_name? Think of 
"tendency_of_X_due_to_emissions_from_Y" where you want to link both the 
compound and the emission sector to the respecitve controlled vocabulary table. 
Then, in another standard_name you will find some marine bacteria or so which 
relate to yet another vocabulary list, and so on. Unless I miss the point here, 
I would still argue that it will be more efficient and less ambiguous if the 
link would be provided in the standard_name table itself.

What do you think?

Cheers,

Martin




Date: Fri, 19 Oct 2012 12:30:42 +0100

From: "Lowry, Roy K." <r...@bodc.ac.uk<mailto:r...@bodc.ac.uk>>

To: "cf-metadata@cgd.ucar.edu<mailto:cf-metadata@cgd.ucar.edu>" 
<cf-metadata@cgd.ucar.edu<mailto:cf-metadata@cgd.ucar.edu>>

Subject: [CF-metadata] Extensions to the Standard Name table

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Dear All,



Martin Schultz was proposing an extension to the Standard Name table to provide 
a means of easily identifying the Standard Names associated with a given 
atmospheric contaminant.  What follows provides an alternative way to address 
his use case.  Go to the URL http://vocab.nerc.ac.uk/sparql/ and copy the 
SPARQL query at the end of this message into the box, choose your output format 
and press 'Get Results'. If you don't want 'carbon monoxide' simply replace 
'Carbon monoxide' by another valid EEA contaminant name.



For the techies on the list, this is done by a federated SPARQL query involving 
SPARQL endpoints on vocabulary servers at BODC and the EEA. This is based on 
string matching, but could be made more robust by implementing an EEA/Standard 
Names mapping in NVS should this be requested by the CF community.



Cheers, Roy.





PREFIX skos: <http://www.w3.org/2004/02/skos/core#>

PREFIX j.0: <http://rdfdata.eionet.europa.eu/airbase/schema/>

PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT ?urie ?labele ?urin ?labeln WHERE {

  BIND("Carbon monoxide" AS ?pollutant)

  SERVICE<http://cr.eionet.europa.eu/sparql>

  {

    ?urie skos:inScheme 
<http://rdfdata.eionet.europa.eu/airquality/components/>.

    ?urie skos:prefLabel ?labele.

    ?urie j.0:pollutant ?pollutant.

  }.

  <http://vocab.nerc.ac.uk/collection/P07/current/> skos:member ?urin.

  ?urin skos:prefLabel ?labeln.

  ?urin skos:definition ?defn.

  FILTER CONTAINS (str(lcase(?defn)),str(lcase(?pollutant)))

}





PD Dr. Martin G. Schultz
IEK-8, Forschungszentrum Jülich
D-52425 Jülich
Ph: +49 2461 61 2831



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