Projects per year
Abstract
The advancements and popularity of Semantic Web technologies in the last decades have led to an exponential adoption and availability of Web-accessible datasets. While most solutions consider such datasets to be static, they often evolve over time. Hence, efficient archiving solutions are needed to meet the users’ and maintainers’ needs. While some solutions to these challenges already exist, standardized benchmarks are needed to systematically test the different capabilities of existing solutions and identify their limitations. Unfortunately, the development of new benchmarks has not kept pace with the evolution of RDF archiving systems. In this paper, we therefore identify the current state of the art in RDF archiving benchmarks and discuss to what degree such benchmarks reflect the current needs of real-world use cases and their requirements. Through this empirical assessment, we highlight the need for the development of more advanced and comprehensive benchmarks that align with the evolving landscape of RDF archiving.
Original language | English |
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Journal | CEUR Workshop Proceedings |
Volume | 3565 |
Pages (from-to) | 50-54 |
Number of pages | 5 |
ISSN | 1613-0073 |
Publication status | Published - 2023 |
Event | Joint of the 7th Workshop on Storing, Querying and Benchmarking Knowledge Graphs and 9th Workshop on Managing the Evolution and Preservation of the Data Web, QuWeDa-MEPDaW 2023 - Athens, Greece Duration: 6 Nov 2023 → 10 Nov 2023 |
Conference
Conference | Joint of the 7th Workshop on Storing, Querying and Benchmarking Knowledge Graphs and 9th Workshop on Managing the Evolution and Preservation of the Data Web, QuWeDa-MEPDaW 2023 |
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Country/Territory | Greece |
City | Athens |
Period | 06/11/2023 → 10/11/2023 |
Bibliographical note
Publisher Copyright:© 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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A Holistic Architecture for Metadata Management in RDF Datasets
Pelgrin, O. P. (PI)
01/09/2019 → …
Project: PhD Project
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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 → 31/10/2024
Project: Research
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