A Community Survey on SHACL and ShEx: Briding Gaps in RDF Validation

2026-06-02

AI Summary

This study addresses the limitations of RDF validation in real-world applications, where inadequate documentation, insufficient tool support, performance bottlenecks, and limited expressiveness hinder knowledge graph data quality. To bridge this gap, the authors conduct the first large-scale community survey targeting both academia and industry, employing an online questionnaire to analyze the adoption, user requirements, and key challenges associated with mainstream validation frameworks such as SHACL and ShEx. The findings uncover critical discrepancies between current RDF validation practices and technological capabilities, identifying four priority directions for improvement: enhanced documentation, optimized toolchains, performance scalability, and language expressiveness. These insights provide empirical grounding and actionable guidance for the future evolution, standardization, and implementation of RDF validation technologies.

Abstract

This paper examines RDF validation practices and challenges to understand stakeholder applications, their needs, and identify areas for improvement in technologies and methodologies, thereby guiding future research and standardization efforts. A community survey was conducted, targeting a diverse group of RDF validation technology users across academia and industry. The survey collected data on current practices, tool usage, perceived benefits, limitations, and desired enhancements to gain a broad overview of the validation landscape. Our analysis shows that while RDF validation is widely adopted and valued for enhancing data quality, significant challenges remain. In particular, users report a need for better documentation, improved tool support, enhanced performance, and greater language expressiveness to handle complex large-scale validation tasks effectively. This work provides crucial insights into the RDF validation landscape, highlighting current practices and key areas for development. It offers a foundation for researchers, developers, and standardization bodies to address current limitations and advance validation technologies, ultimately improving data quality and usability in knowledge graphs.

Problem

• RDF validation
• SHACL
• ShEx
• data quality
• knowledge graphs

Innovation

• RDF validation
• SHACL
• ShEx
• community survey
• knowledge graph