Dear Paul, others, On Fri, Apr 24, 2015 at 4:39 PM, Paul Houle <ontology2@gmail.com> wrote: > Also I find the "no special hardware requirements" thing to be strange, > probably because it ought to be defined in terms of "I have a machine with > these specific specifications". For instance, if you had a machine with > 32GB of RAM (which is pretty affordable if you don't pay OEM prices) you > could load a billion triples into a triple store. If your machine is a > hand-me-down laptop from a salesman who couldn't sell that has just 4GB of > RAM you are in a very different situation. The method that Laurens and I are using is a combination of LOD Laundromat <http://lodlaundromat.org/> (ISWC paper <http://link.springer.com/chapter/10.1007/978-3-319-11964-9_14>) created by us and Linked Data Fragments <http://linkeddatafragments.org/> (ISWC paper <http://www.researchgate.net/profile/Ruben_Verborgh/publication/264274086_Web-Scale_Querying_through_Linked_Data_Fragments/links/53f498b10cf2fceacc6e918d.pdf>) created by the research group of Ruben Verborgh. Both approaches were integrated earlier this year (ESWC paper <http://ruben.verborgh.org/publications/rietveld_eswc_2015/>) resulting in a large-scale platform for LOD processing that can scale without noticeable memory consumption. All scalable parameters are ultimately related to disk-space, which is relatively cheap and easy to scale. The LOD Laundromat indeed does not currently serve "the complete LOD Cloud" but a subset consisting of 37B triples). Due to its architectural underpinnings there seems to be no inherent reason why it could not serve the complete LOD Cloud. --- Best regards, Wouter B eek. E-mail: w.g.j.beek@vu.nl WWW: www.wouterbeek.com Tel.: 0647674624
Received on Tuesday, 28 April 2015 01:40:38 UTC