HDTQ: Managing RDF Datasets in Compressed Space

author: Javier David Fernández García, Vienna University of Economics and Business
published: July 10, 2018,   recorded: June 2018,   views: 2
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

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.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: