On 3/31/16 1:30 PM, Jörn Hees wrote:
> Hi,
>
> i developed some machine learning algorithms that i'd like to run against
> various datasets.
> Many of them provide Virtuoso powered SPARQL endpoints online, but running my
> algorithms against them would for sure not be considered "fair use".
>
> Some datasets provide dumps, so i'm able to play nice, load the dumps on a
> local Virtuoso instance and torture that local instance with my algorithms.
>
> How can i do something similar in case there is no dump available for
> download, but only a SPARQL endpoint?
>
> I was thinking about issuing a `construct where { ?s ?p ?o } limit X offset
> Y` and stepping through the endpoint like that once, but the bigger the
> offset, the slower the response time:
>
> http://dbpedia.org/sparql?default-graph-uri=http%3A%2F%2Fdbpedia.org&qtxt=select+*+where+{%3Fs+%3Fp+%3Fo.}+limit+10000+offset+400020000&format=text%2Fhtml&CXML_redir_for_subjs=121&CXML_redir_for_hrefs=&timeout=30000&debug=on
>
> Any suggestions how to improve this and do this in a "nice" way?
> Also maybe without the danger of skipping a lot of data by different orders?
>
> Best,
> JörnHow are you arriving at data devoid or metadata about its origins? You would be better served, ultimately, instantiating a dedicated Virtuoso instance in the cloud for your specific needs. This instance could load datasets from wherever, using some of the existing endpoints (DBpedia and others) as a mechanism for exposing provenance data etc.. There is no nice way of trying to dump all the data from an existing SPARQL endpoint. Regards, Kingsley Idehen Founder & CEO OpenLink Software Company Web: http://www.openlinksw.com Personal Weblog 1: http://kidehen.blogspot.com Personal Weblog 2: http://www.openlinksw.com/blog/~kidehen Twitter Profile: https://twitter.com/kidehen Google+ Profile: https://plus.google.com/+KingsleyIdehen/about LinkedIn Profile: http://www.linkedin.com/in/kidehen Personal WebID: http://kingsley.idehen.net/dataspace/person/kidehen#this
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