Abstract
Knowledge Graphs have been successfully adopted in recent years, existing general-purpose ones, like Wikidata, as well as domain-specific ones, like UniProt. Their increasing size poses new challenges to their practical usage. As an example, Wikidata has been growing the size of its contents and their data since its inception making it difficult to download and process its data. Although the structure of Wikidata items is flexible, it tends to be heterogeneous: the shape of an entity representing a human is distinct from that of a mountain. Recently, Wikidata adopted Entity Schemas to facilitate the definition of different schemas using Shape Expressions, a language that can be used to describe and validate RDF data. In this paper, we present an approach to obtain subsets of knowledge graphs based on Shape Expressions that use an implementation of the Pregel algorithm implemented in Rust. We have applied our approach to obtain subsets of Wikidata and UniProt and present some of these experiments’ results.
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Acknowledgements
This project has received funding from NumFOCUS, a non-profit organization promoting open-source scientific projects, and has been supported by the ANGLIRU project, funded by the Spanish Agency for Research. The opinions and arguments employed herein do not reflect the official views of these organizations.
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Préstamo, Á.I., Gayo, J.E.L. (2023). Using Pregel to Create Knowledge Graphs Subsets Described by Non-recursive Shape Expressions. In: Ortiz-Rodriguez, F., Villazón-Terrazas, B., Tiwari, S., Bobed, C. (eds) Knowledge Graphs and Semantic Web. KGSWC 2023. Lecture Notes in Computer Science, vol 14382. Springer, Cham. https://doi.org/10.1007/978-3-031-47745-4_10
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