Pipelining SPARQL queries in memory with the rdflib Python library
Using retrieved data to make more queries.
Last month in Dividing and conquering SPARQL endpoint retrieval I described how you can avoid timeouts for certain kinds of SPARQL endpoint queries by first querying for the resources that you want to know about and then querying for more data about those resources a subset at a time using the VALUES keyword. (The example query retrieved data, including the latitude and longitude, about points within a specified city.) I built my demo with some shell scripts, some Perl scripts, and a bit of spit…
