解决知识图谱中约束校验与本体融合的语义冲突问题
SHACL Validation in the Presence of Ontologies: Semantics and Rewriting Techniques
- 基于核心通用模型定义本体环境下的SHACL校验语义
- 提出有限表示方法，将复杂校验转化为标准校验
- 证明简单本体下校验为指数时间完备，适合推理系统开发者
SHACL与OWL是W3C推荐的RDF数据管理标准。两者共享诸多特性，但核心差异在于：OWL基于开放世界假设，支持从不完整数据推断事实；而SHACL作为约束语言，采用封闭世界假设，要求数据完整。二者的结合极具吸引力，但语义鸿沟带来重大挑战。本文提出一种基于核心通用模型的本体环境下SHACL校验语义。针对数据可处理描述逻辑Horn-ALCHIQ中的本体，我们提供构建此类模型的技术。进一步，利用该模型的有限表示，发展出将本体存在下的SHACL校验转化为标准校验的重写技术。最后，我们分析了该校验问题的复杂度：即使在极简本体下，问题仍为EXPTIME-complete；在数据复杂度下则为PTIME-complete。
原文摘要 · Abstract (English)
SHACL and OWL are two prominent W3C standards for managing RDF data. These languages share many features, but they have one fundamental difference: OWL, designed for inferring facts from incomplete data, makes the open-world assumption, whereas SHACL is a constraint language that treats the data as complete and must be validated under the closed-world assumption. The combination of both formalisms is very appealing and has been called for, but their semantic gap is a major challenge, semantically and computationally. In this paper, we advocate a semantics for SHACL validation in the presence of ontologies based on core universal models. We provide a technique for constructing these models for ontologies in the rich data-tractable description logic Horn-ALCHIQ. Furthermore, we use a finite representation of this model to develop a rewriting technique that reduces SHACL validation in the presence of ontologies to standard validation. Finally, we study the complexity of SHACL validation in the presence of ontologies, and show that even very simple ontologies make the problem EXPTIME-complete, and PTIME-complete in data complexity.
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