Abstract

Because of the flexibility and expressiveness of their model, Knowledge Graphs (KGs) have received
increasing interest. These resources are usually represented in RDF and stored in specialized data
management systems called triplestores. Yet, while there exists a multitude of such systems, exploiting
varying data representation and indexing schemes, it is unclear which of the many design choices are
the most effective for a given database and query workload. Thus, first, we introduce a set of 20 access
patterns, which we identify within 6 categories, adopted to analyze the needs of a given query workload.
Then, we identify a novel three-dimensional design space for RDF data representations built on the
dimensions of subdivision, redundancy, and compression of data. This design space maps the trade-offs
between different RDF data representations employed to store RDF data within a triplestore. Thus, each
of the required access patterns is compared against its compatibility with a given data representation. As
we show, this approach allows identifying both the most effective RDF data representation for a given
query workload as well as unexplored design solutions.
OriginalsprogEngelsk
TidsskriftCEUR Workshop Proceedings
Vol/bind3194
ISSN1613-0073
StatusUdgivet - 2022
Begivenhed30th Italian Symposium on Advanced Database Systems, SEBD 2022 - Tirrenia, Italien
Varighed: 19 jun. 202220 jun. 2022

Konference

Konference30th Italian Symposium on Advanced Database Systems, SEBD 2022
Land/OmrådeItalien
ByTirrenia
Periode19/06/202220/06/2022

Fingeraftryk

Dyk ned i forskningsemnerne om 'Understanding RDF Data Representations in Triplestores'. Sammen danner de et unikt fingeraftryk.

Citationsformater