一次改写，任意地方验证：生成支持OWL的SHACL约束（扩展版）

中文摘要 AI 辅助

形状约束语言（SHACL）是W3C推荐的、用于表达RDF图上称为“形状”的语法约束的标准，SHACL验证器用于测试给定图是否符合该形状。然而，RDF图常附带OWL本体，需考虑其隐含知识，传统方法是先应用推理再对结果执行约束检查，常使用不同技术，导致流程低效且易出错。为解决此问题，本文提出将OWL公理内化为SHACL约束，构建一种改写方法，其输入为形状和OWL EL⁻本体（OWL EL的一个片段，限制存在量词约束的使用），输出为SHACL约束。该输出可由任何支持SHACL核心的验证器评估，无需推理支持，且结果与传统方法一致。本文将该翻译实现与依次应用最先进推理器和验证器的情况、以及内置推理支持的验证器分别对比评估，在基准测试中表明，本文方法在查找违反情况方面通常比顺序方法更高效，从而提供了一种强大工具，简化了推理与验证的结合。

英文摘要

The Shapes Constraint Language (SHACL) is a W3C recommendation to express syntactic constraints, called shapes, on RDF graphs. SHACL validators are used to test whether a given graph adheres to such a shape. However, RDF graphs often come with OWL ontologies, whose implicit knowledge needs to be taken into account. This is classically handled by first applying reasoning and then performing the constraint checking on the results, often using different technologies which makes the process inefficient and vulnerable for mistakes. To overcome this, we propose to internalise the OWL axioms in the SHACL constraints; we construct a rewriting which takes as input both shapes and an OWL EL$^-$ ontology -- a fragment of OWL EL restricting the usage of existential restrictions -- and produces SHACL constraints. This output can then be evaluated by any validator supporting SHACL core regardless of its reasoning support, while yielding the same results as the traditional approach. The implementation of our translation is evaluated both against applying state-of-the-art reasoners and validators consecutively, as against validators with built-in reasoning support. For our benchmark, we show that our approach is in general more efficient in finding violations compared to the sequential approach, thus providing a powerful tool which simplifies combining reasoning with validation.

发表机构

• Institute of Logic and Computation, TU Wien（维也纳技术大学逻辑与计算研究所）
• TU Dresden（德累斯顿工业大学）
• ScaDS.AI, Dresden/Leipzig（德累斯顿/莱佩斯人工智能服务中心）

机构由 AI 辅助整理，请以论文原文为准。

补充信息

备注

Technical report of our ISWC'26 paper