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.
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Fernández, J.D., Martínez-Prieto, M.A., Arias, M., Gutierrez, C., Álvarez-García, S., Brisaboa, N.R. (2011). Lightweighting the Web of Data through Compact RDF/HDT. In: Lozano, J.A., Gámez, J.A., Moreno, J.A. (eds) Advances in Artificial Intelligence. CAEPIA 2011. Lecture Notes in Computer Science(), vol 7023. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25274-7_49
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DOI: https://doi.org/10.1007/978-3-642-25274-7_49
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