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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.
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 language | English |
|---|---|
| Journal | CEUR Workshop Proceedings |
| Volume | 3194 |
| ISSN | 1613-0073 |
| Publication status | Published - 2022 |
| Event | 30th Italian Symposium on Advanced Database Systems, SEBD 2022 - Tirrenia, Italy Duration: 19 Jun 2022 → 20 Jun 2022 |
Conference
| Conference | 30th Italian Symposium on Advanced Database Systems, SEBD 2022 |
|---|---|
| Country/Territory | Italy |
| City | Tirrenia |
| Period | 19/06/2022 → 20/06/2022 |
Fingerprint
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Poul Due Jensen Professorate in Big Data and Artificial Intelligence
Hose, K. (PI), Jendal, T. E. (Project Participant) & Hansen, E. R. (Project Participant)
01/11/2019 → 31/12/2025
Project: Research
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EDAO: EDAO: Example Driven Analytics for Open Knowledge Graphs
Lissandrini, M. (PI), Pedersen, T. B. (Supervisor) & Hose, K. (Other)
15/09/2019 → 14/09/2021
Project: Research
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Research output
- 1 Journal article
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A design space for RDF data representations
Sagi, T., Lissandrini, M., Pedersen, T. B. & Hose, K., 21 Jan 2022, In: The VLDB Journal. 31, 2, p. 347-373 27 p.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile17 Citations (Scopus)153 Downloads (Pure)