Real World example: Billion Triple 2010<br />Where is the metadata?<br />Who did publish this?<br />Do I have all the data?<br />?<br /><br />PUBLICATION<br />EXCHANGE<br />RDF<br />RDF<br />RDF<br />gzip<br />RDF<br />RDF<br />RDF<br />gzip<br /><br />basicoperations<br />Pag 3<br />
Needs<br />Theaims of theformat are: <br /><ul><li>Clean publication
HDT And SPARQL<br /><ul><li>SPARQL can make use of some interesting features in HDT:
Subject-object JOINs resolution can profit from the common naming in the dictionary, as the elements are correctly and quickly localized in the top IDs.
Algorithm 1 can response basic ASK queries of SPARQL for patterns (s,p,o), (s,?p,?o) and (s,p,?o).
Algorithm 1 can response basic CONSTRUCT query of SPARQL for simple WHERE patterns (s,p,o), (s,?p,?o) and (s,p,?o).The resultant is a RDF HDT graph.</li></ul>Note: The S-P-O Adjacency List order is assumed. The Algorithm1 and the response patterns vary for alternative representations S-O-P AL, P-S-O, P-O-S, O-P-S AL and O-S-P AL.<br />Pag 30<br />
Conclusions<br /><ul><li>RDF publication and exchange at large scale are seriously compromised by the scalability drawbacks of current RDF formats
lack of structure, metadata information and native operations over the data