Formalizing and validating Wikidata’s property constraints using SHACL and SPARQL

In this paper, we delve into the crucial role of constraints in maintaining data integrity in knowledge graphs with a specific focus on Wikidata, one of the most extensive collaboratively maintained open data knowledge graphs on the Web. The World Wide Web Consortium (W3C) recommends the Shapes Constraint Language (SHACL) as the constraint language for validating Knowledge Graphs, which comes in two different levels of expressivity, SHACL-Core, as well as SHACL-SPARQL. Despite the availability of SHACL, Wikidata currently represents its property constraints through its own RDF data model, which relies on Wikidata’s specific reification mechanism based on authoritative namespaces, and – partially ambiguous – natural language definitions. In the present paper, we investigate whether and how the semantics of Wikidata property constraints, can be formalized using SHACL-Core, SHACL-SPARQL, as well as directly as SPARQL queries. While the expressivity of SHACL-Core turns out to be insufficient for expressing all Wikidata property constraint types, we present SPARQL queries to identify violations for all 32 current Wikidata constraint types. We compare the semantics of this unambiguous SPARQL formalization with Wikidata’s violation reporting system and discuss limitations in terms of evaluation via Wikidata’s public SPARQL query endpoint, due to its current scalability. Our study, on the one hand, sheds light on the unique characteristics of constraints defined by the Wikidata community, in order to improve the quality and accuracy of data in this collaborative knowledge graph. On the other hand, as a “byproduct”, our formalization extends existing benchmarks for both SHACL and SPARQL with a challenging, large-scale real-world use case.

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Publication Details

Journal
Semantic Web
Published
2024-08-23
DOI
https://doi.org/10.3233/sw-243611
Citations
5
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
1.74
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article

Formalizing and validating Wikidata’s property constraints using SHACL and SPARQL

Shqiponja Ahmetaj, Nicolas Ferranti, Jairo Francisco de Souza, Axel Polleres
5 citations
Semantic Web
Semantic Web and Ontologies
1.74
article

Formalizing and validating Wikidata’s property constraints using SHACL and SPARQL

Shqiponja Ahmetaj, Nicolas Ferranti, Jairo Francisco de Souza, Axel Polleres
article en
5 citations

Abstract

In this paper, we delve into the crucial role of constraints in maintaining data integrity in knowledge graphs with a specific focus on Wikidata, one of the most extensive collaboratively maintained open data knowledge graphs on the Web. The World Wide Web Consortium (W3C) recommends the Shapes Constraint Language (SHACL) as the constraint language for validating Knowledge Graphs, which comes in two different levels of expressivity, SHACL-Core, as well as SHACL-SPARQL. Despite the availability of SHACL, Wikidata currently represents its property constraints through its own RDF data model, which relies on Wikidata’s specific reification mechanism based on authoritative namespaces, and – partially ambiguous – natural language definitions. In the present paper, we investigate whether and how the semantics of Wikidata property constraints, can be formalized using SHACL-Core, SHACL-SPARQL, as well as directly as SPARQL queries. While the expressivity of SHACL-Core turns out to be insufficient for expressing all Wikidata property constraint types, we present SPARQL queries to identify violations for all 32 current Wikidata constraint types. We compare the semantics of this unambiguous SPARQL formalization with Wikidata’s violation reporting system and discuss limitations in terms of evaluation via Wikidata’s public SPARQL query endpoint, due to its current scalability. Our study, on the one hand, sheds light on the unique characteristics of constraints defined by the Wikidata community, in order to improve the quality and accuracy of data in this collaborative knowledge graph. On the other hand, as a “byproduct”, our formalization extends existing benchmarks for both SHACL and SPARQL with a challenging, large-scale real-world use case.

Semantic Web
Universidade Federal de Juiz de Fora (BR), Vienna University of Economics and Business (AT), TU Wien (AT), Complexity Science Hub (AT)
Openalex Percentile: Top 13%
Semantic Web and Ontologies
1.74
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