PUBLICATION
Facilitating RDF Querying in Research Data Management through ShEx-Based SPARQL Query Construction
Type
Workshop Paper
Year
2025
Authors
Research Area
Web Engineering
Event
Natural Scientific Language Processing and Research Knowledge Graphs (NSLP 2025)
Published in
2nd International Workshop on Natural Scientific Language Processing and Research Knowledge Graphs (NSLP 2025), co-located with ESWC 2025, June 01–02, 2025, Portorož, Slovenia
Download
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.