Facilitating RDF Querying in Research Data Management through ShEx-Based SPARQL Query Construction

Metadata about research data is increasingly represented using the Resource Description Framework (RDF) across diverse domains, as RDF offers a structured yet flexible way to represent and query data. However, querying RDF data can be challenging, as users need to be proficient in the SPARQL query language to create syntactically correct queries. Furthermore, users must be familiar with the ontologies used for describing the desired data to choose appropriate classes and properties for their queries. As a result, the manual query construction process is both time-consuming and error-prone. To address this, we propose an approach that leverages schemas in the Shape Expressions Language (ShEx) as blueprints for constructing SPARQL queries. This approach is demonstrated using two case studies in the research data domain --- one focusing on image data and one focusing on survey data --- where each data type is described in a respective ShEx shape. We then use our ShEx2SPARQL tool to automatically translate a ShEx schema into a SPARQL query, thereby relieving users of the burden of manual query construction and enhancing the accessibility of RDF data.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-01
DOI
https://doi.org/10.5281/zenodo.17380454
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
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article

Facilitating RDF Querying in Research Data Management through ShEx-Based SPARQL Query Construction

Zenodo (CERN European Organization for Nuclear Research)
Semantic Web and Ontologies
article

Facilitating RDF Querying in Research Data Management through ShEx-Based SPARQL Query Construction

article en

Abstract

Metadata about research data is increasingly represented using the Resource Description Framework (RDF) across diverse domains, as RDF offers a structured yet flexible way to represent and query data. However, querying RDF data can be challenging, as users need to be proficient in the SPARQL query language to create syntactically correct queries. Furthermore, users must be familiar with the ontologies used for describing the desired data to choose appropriate classes and properties for their queries. As a result, the manual query construction process is both time-consuming and error-prone. To address this, we propose an approach that leverages schemas in the Shape Expressions Language (ShEx) as blueprints for constructing SPARQL queries. This approach is demonstrated using two case studies in the research data domain --- one focusing on image data and one focusing on survey data --- where each data type is described in a respective ShEx shape. We then use our ShEx2SPARQL tool to automatically translate a ShEx schema into a SPARQL query, thereby relieving users of the burden of manual query construction and enhancing the accessibility of RDF data.

Zenodo (CERN European Organization for Nuclear Research)
Chemnitz University of Technology (DE)
Decent work and economic growth
Openalex Percentile: Top 24%
Semantic Web and Ontologies
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Facilitating RDF Querying in Research Data Management through ShEx-Based SPARQL Query Construction · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS