Rohde, P.D.; Vidal, M.-E.: SHACL constraint validation during SPARQL query processing. In: Bernstein, Philip A.; Rabl, Tilmann (Eds.): VLDB-PhD 2021 : VLDB 2021 PhD Workshop : proceedings of the VLDB 2021 PhD Workshop, co-located with the 47th International Conference on Very Large Databases (VLDB 2021). Aachen, Germany : RWTH Aachen, 2021 (CEUR Workshop Proceedings ; 2971), 05.
Zusammenfassung: |
The importance of knowledge graphs is increasing. Due to their application in more and more real-world use-cases the data quality issue has to be addressed. The Shapes Constraint Language (SHACL) is the W3C recommendation language for defining integrity constraints over knowledge graphs expressed in the Resource Description Framework (RDF). Annotating SPARQL query results with metadata from the SHACL validation provides a better understanding of the knowledge graph and its data quality. We propose a query engine that is able to efficiently evaluate which instances in the knowledge graph fulfill the requirements from the SHACL shape schema and annotate the SPARQL query result with this metadata. Hence, adding the dimension of explainability to SPARQL query processing. Our preliminary analysis shows that the proposed optimizations performed for SHACL validation during SPARQL query processing increase the performance compared to a naive approach. However, in some queries the naive approach outperforms the optimizations. This shows that more work needs to be done in this topic to fully comprehend all impacting factors and to identify the amount of overhead added to the query execution.
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Lizenzbestimmungen: |
CC BY 4.0 Unported - https://creativecommons.org/licenses/by/4.0
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Publikationstyp: |
BookPart |
Publikationsstatus: |
publishedVersion |
Erstveröffentlichung: |
2021 |
Schlagwörter (englisch): |
Knowledge graph, Metadata, Semantic Web, Constraint language, Constraints validations
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Fachliche Zuordnung (DDC): |
004 | Informatik, 020 | Bibliotheks- und Informationswissenschaft
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Kontrollierte Schlagwörter: |
Konferenzschrift
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