Paul Houle wrote:
> Jürgen Jakobitsch wrote:
>   
>> predication : in a couple of years, everything will be rdf - but 
>> vocabularies will only be understood
>>               in limited geographical areas - gone be the vision of global 
>> communication.
>>
>> http://dbpedia.org/page/New_York_City -> dbpprop:latd (xsd:integer)
>> http://dbpedia.org/page/Paris -> dbpprop:latLong -> 
>> dbpedia:Paris/latLong/coord -> dbpprop:coordProperty (some xsd:integer - not 
>> interpretable)
>> http://dbpedia.org/page/Berlin -> dbpprop:latD -> (xsd:double)
>> http://dbpedia.org/page/Oslo -> dbpprop:latDeg -> (xsd:integer)
>> http://dbpedia.org/page/Babylon -> geo:lat -> (xsd:float)
>>
>>   
>>     
>     This is just the beginning of problems that you face if you try to 
> do serious geospatial reasoning with dbpedia data (or even try to draw 
> maps.)
>
>     Imagine the meaning of a point coordinate for new york city,  as 
> compared to a point coordinate for the statue of liberty.  The statue of 
> liberty fills a footprint on the ground which is about 10 m in radius.  
> It's reasonable to pretend that it's a point if you're drawing a map of 
> NYC.  NYC represents a ground footprint that is more like 10 km in 
> radius.  At best,  you can represent it with a centroid or a point 
> that's particularly significant (Google maps,  for instance,  locates 
> New York City at the 42nd and 7th intersection by the Port Authority Bus 
> Terminal;)  the point for NYC is pretty much meaningless if you're 
> drawing a map of the city,  but it would be useful if you were drawing a 
> map of the Northeastern US.
>
>     On top of that,  there are all kinds of errors in coordinates that 
> come from Wikipedia.  Last time I looked,  I found a South Carolina 
> cotton plantation out in Canada's Hudson bay in the "Wikipedia" layer of 
> Google Maps.  I don't know about dbpedia 3.3,  but I do know that 
> dbpedia 3.2 thinks that the Staten Island Railway is about a km east of 
> where it really is,  situating it in the middle of New York Harbor 
> (running right under the Tappan Zee Bridge.)
>
>     Similarly,  there are places in wikipedia (freebase too) that have 
> addresses but no coordinates.  These can be put through a geocoder and 
> can have coordinates attached. 
>
>     I've brought up different types of issues:
>
> (i) insufficient data types:  "New York City" would be best represented 
> at a region (a polygon or union of polygons) rather than as a point.
> (ii) data quality:  how accurate does a point claim to be?  what do we 
> do with the occasional point that's wildly wrong
>
>     At this point in time,  it's not practical to build geospatial 
> reasoning systems based on amnesiac mashups off SPARQL endpoints.
>
>     A practical geospatial system based on linked data is going to need 
> to reconcile inconsistent terminology,  clean up data,  and combine data 
> from different sources.  For instance,  both Yahoo and the US Census can 
> be used as a source for political area boundaries.  The problems that 
> you're talking about are just the first ones that turn up on the journey ;-)
>   
Paul,

I would qualify the problem as being specific to the DBpedia Linked Data 
Space rather than Linked Data in general :-)

Also, how does the geonames data space fair re. your analysis?

You are highlighting what could become anecdotal material re. why domain 
specific data spaces are important, in this case, one that's totally 
about data for reliable geo informatics etc..

Kingsley
>
>
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-- 


Regards,

Kingsley Idehen       Weblog: http://www.openlinksw.com/blog/~kidehen
President & CEO 
OpenLink Software     Web: http://www.openlinksw.com





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