Scaling large RDF archives to very long histories
- Author
- Olivier Pelgrin, Ruben Taelman (UGent) , Luis Galárraga and Katja Hose
- Organization
- Abstract
- In recent years, research in RDF archiving has gained traction due to the ever-growing nature of semantic data and the emergence of community-maintained knowledge bases. Several solutions have been proposed to manage the history of large RDF graphs, including approaches based on independent copies, time-based indexes, and change-based schemes. In particular, aggregated changesets have been shown to be relatively efficient at handling very large datasets. However, ingestion time can still become prohibitive as the revision history increases. To tackle this challenge, we propose a hybrid storage approach based on aggregated changesets, snapshots, and multiple delta chains. We evaluate different snapshot creation strategies on the BEAR benchmark for RDF archives, and show that our techniques can speed up ingestion time up to two orders of magnitude while keeping competitive performance for version materialization and delta queries. This allows us to support revision histories of lengths that are beyond reach with existing approaches.
- Keywords
- STORAGE
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01GYHHJ97QMM2A9AW2CPTAHZ0H
- MLA
- Pelgrin, Olivier, et al. “Scaling Large RDF Archives to Very Long Histories.” 2023 IEEE 17th International Conference on Semantic Computing (ICSC), IEEE, 2023, pp. 41–48, doi:10.1109/icsc56153.2023.00013.
- APA
- Pelgrin, O., Taelman, R., Galárraga, L., & Hose, K. (2023). Scaling large RDF archives to very long histories. 2023 IEEE 17th International Conference on Semantic Computing (ICSC), 41–48. https://doi.org/10.1109/icsc56153.2023.00013
- Chicago author-date
- Pelgrin, Olivier, Ruben Taelman, Luis Galárraga, and Katja Hose. 2023. “Scaling Large RDF Archives to Very Long Histories.” In 2023 IEEE 17th International Conference on Semantic Computing (ICSC), 41–48. IEEE. https://doi.org/10.1109/icsc56153.2023.00013.
- Chicago author-date (all authors)
- Pelgrin, Olivier, Ruben Taelman, Luis Galárraga, and Katja Hose. 2023. “Scaling Large RDF Archives to Very Long Histories.” In 2023 IEEE 17th International Conference on Semantic Computing (ICSC), 41–48. IEEE. doi:10.1109/icsc56153.2023.00013.
- Vancouver
- 1.Pelgrin O, Taelman R, Galárraga L, Hose K. Scaling large RDF archives to very long histories. In: 2023 IEEE 17th International Conference on Semantic Computing (ICSC). IEEE; 2023. p. 41–8.
- IEEE
- [1]O. Pelgrin, R. Taelman, L. Galárraga, and K. Hose, “Scaling large RDF archives to very long histories,” in 2023 IEEE 17th International Conference on Semantic Computing (ICSC), Laguna Hills, USA, 2023, pp. 41–48.
@inproceedings{01GYHHJ97QMM2A9AW2CPTAHZ0H,
abstract = {{In recent years, research in RDF archiving has gained traction due to the ever-growing nature of semantic data and the emergence of community-maintained knowledge bases. Several solutions have been proposed to manage the history of large RDF graphs, including approaches based on independent copies, time-based indexes, and change-based schemes. In particular, aggregated changesets have been shown to be relatively efficient at handling very large datasets. However, ingestion time can still become prohibitive as the revision history increases. To tackle this challenge, we propose a hybrid storage approach based on aggregated changesets, snapshots, and multiple delta chains. We evaluate different snapshot creation strategies on the BEAR benchmark for RDF archives, and show that our techniques can speed up ingestion time up to two orders of magnitude while keeping competitive performance for version materialization and delta queries. This allows us to support revision histories of lengths that are beyond reach with existing approaches.}},
author = {{Pelgrin, Olivier and Taelman, Ruben and Galárraga, Luis and Hose, Katja}},
booktitle = {{2023 IEEE 17th International Conference on Semantic Computing (ICSC)}},
isbn = {{9781665482639}},
issn = {{2325-6516}},
keywords = {{STORAGE}},
language = {{eng}},
location = {{Laguna Hills, USA}},
pages = {{41--48}},
publisher = {{IEEE}},
title = {{Scaling large RDF archives to very long histories}},
url = {{http://doi.org/10.1109/icsc56153.2023.00013}},
year = {{2023}},
}
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