Quotation Fernandez Garcia, Javier David, Kirrane, Sabrina, Polleres, Axel, Steyskal, Simon. 2020. HDT crypt: Compression and Encryption of RDF Datasets. Semantic Web. 11 (2), 337-359.




The publication and interchange of RDF datasets online has experienced significant growth in recent years, promoted by different but complementary efforts, such as Linked Open Data, the Web of Things and RDF stream processing systems. However, the current Linked Data infrastructure does not cater for the storage and exchange of sensitive or private data. On the one hand, data publishers need means to limit access to confidential data (e.g. health, financial, personal, or other sensitive data). On the other hand, the infrastructure needs to compress RDF graphs in a manner that minimises the amount of data that is both stored and transferred over the wire. In this paper, we demonstrate how HDT - a compressed serialization format for RDF - can be extended to cater for supporting encryption. We propose a number of different graph partitioning strategies and discuss the benefits and tradeoffs of each approach.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Semantic Web
Citation Index SCI
WU-Journal-Rating new INF-A
Language English
Title HDT crypt: Compression and Encryption of RDF Datasets
Volume 11
Number 2
Year 2020
Page from 337
Page to 359
Reviewed? Y
URL http://semantic-web-journal.net/content/hdt-crypt-compression-and-encryption-rdf-datasets#
DOI na
Open Access Y
Open Access Link http://semantic-web-journal.net/content/hdt-crypt-compression-and-encryption-rdf-datasets#


Fernandez Garcia, Javier David (Former researcher)
Kirrane, Sabrina (Details)
Polleres, Axel (Details)
Steyskal, Simon (Siemens AG, Austria)
Institute for Data, Process and Knowledge Management (AE Polleres) (Details)
Institute for Data, Process and Knowledge Management IN (Details)
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