@inproceedings{rein-etal-2018ESWC,
 title = {{HDTQ}: Managing {RDF} Datasets in Compressed Space},
 year = 2018,
 author = {Javier D. Fernandez and Miguel A. Mart\'inez-Prieto and Axel Polleres and Julian Reindorf},
 abstract ={HDT (Header-Dictionary-Triples) is a well-known compressed representation of RDF data that supports retrieval features without prior decompression. Yet, RDF datasets often contain additional graph information, such as the origin, version or validity time of a triple. Traditional HDT is not capable of handling this additional parameter(s). This work introduces HDTQ (HDT Quads), an extension of HDT, which is able to represent quadruples (or quads) while still being highly compact and \queryable{}. Two approaches of this extension, Annotated Triples and Annotated Graphs, are introduced and their performance is compared to the leading open-source RDF stores on the market, Results show that HDTQ achieves the best compression rates and is a competitive alternative to well-established systems.},
booktitle = {Proceedings of the 15th European Semantic Web Conference (ESWC2018)},
series = LNCS,
volume = 10843,
publisher = {Springer},
url = {http://polleres.net/publications/fern-etal-ESWC2018.pdf},
doi = {https://doi.org/10.1007/978-3-319-93417-4_13},
day = {3--7},
month = jun,
editor = {Aldo Gangemi and Roberto Navigli and Maria-Esther Vidal and Pascal Hitzler and Raphaël Troncy and Laura Hollink and Anna Tordai and Mehwish Alam},
pages={191--208},
Address = {Heraklion, Greece},
}

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A.","Polleres, A.","Reindorf, J."],"year":2018,"bibtype":"inproceedings","biburl":"www.polleres.net/mypublications.bib","bibdata":{"bibtype":"inproceedings","type":"inproceedings","title":"HDTQ: Managing RDF Datasets in Compressed Space","year":"2018","author":[{"firstnames":["Javier","D."],"propositions":[],"lastnames":["Fernandez"],"suffixes":[]},{"firstnames":["Miguel","A."],"propositions":[],"lastnames":["Martínez-Prieto"],"suffixes":[]},{"firstnames":["Axel"],"propositions":[],"lastnames":["Polleres"],"suffixes":[]},{"firstnames":["Julian"],"propositions":[],"lastnames":["Reindorf"],"suffixes":[]}],"abstract":"HDT (Header-Dictionary-Triples) is a well-known compressed representation of RDF data that supports retrieval features without prior decompression. Yet, RDF datasets often contain additional graph information, such as the origin, version or validity time of a triple. Traditional HDT is not capable of handling this additional parameter(s). 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Fernandez and Miguel A. Mart\\'inez-Prieto and Axel Polleres and Julian Reindorf},\n abstract ={HDT (Header-Dictionary-Triples) is a well-known compressed representation of RDF data that supports retrieval features without prior decompression. Yet, RDF datasets often contain additional graph information, such as the origin, version or validity time of a triple. Traditional HDT is not capable of handling this additional parameter(s). This work introduces HDTQ (HDT Quads), an extension of HDT, which is able to represent quadruples (or quads) while still being highly compact and \\queryable{}. 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