Lightweighting the web of data through compact RDF/HDT

Authors:
Javier D. Fernández;Miguel A. Martínez-Prieto;Mario Arias;Claudio Gutierrez;Sandra Álvarez-García;Nieves R. Brisaboa
Affiliations:
Universidad de Valladolid, España;Universidad de Valladolid, España and Universidad de Chile, Chile;Universidad de Valladolid, España;Universidad de Chile, Chile;Universidade da Coruña, España;Universidade da Coruña, España
Venue:
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
Year:
2011

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Abstract

The Web of Data is producing large RDF datasets from diverse fields. The increasing size of the data being published threatens to make these datasets hardly to exchange, index and consume. This scalability problem greatly diminishes the potential of interconnected RDF graphs. The HDT format addresses these problems through a compact RDF representation, that partitions and efficiently represents three components: Header (metadata), Dictionary (strings occurring in the dataset), and Triples (graph structure). This paper revisits the format and exploits the latest findings in triples indexing for querying, exchanging and visualizing RDF information at large scale.