Exchange and Consumption of Huge RDF Data

Presented at: 9th Extended Semantic Web Conference (ESWC2012)

by Miguel A. Martinez-Prieto, Mario Arias Gallego, Javier D. Fernández

Huge RDF datasets are currently exchanged on textual RDF formats, hence consumers need to post-process them through RDF stores for local consumption, such as reasoning/integration and SPARQL query. This results in a painful task which requires a great effort in terms of time and computational resources. A first approach to lightweight data exchange is a compact (binary) RDF serialization format called HDT. In this paper, we focus on enhancing the exchanged data in order to optimize the consumption without the need of "unpacking" the data. This is done by post-processing the HDT, enhancing the data with additional structures which allow basic forms of SPARQL queries. Experiments show that i) with an exchanging efficiency that outperforms universal compression, ii) post-processing now becomes a fast process which iii) provides competitive query performance at consumption.

Keywords: RDF consumption, RDF exchange, RDF store, SPARQL

Resource URI on the dog food server:

Explore this resource elsewhere: