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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.
Original languageEnglish
JournalCEUR Workshop Proceedings
Publication statusPublished - 2022
Event30th Italian Symposium on Advanced Database Systems, SEBD 2022 - Tirrenia, Italy
Duration: 19 Jun 202220 Jun 2022


Conference30th Italian Symposium on Advanced Database Systems, SEBD 2022


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