Abstract
Metamodeling is a general approach to expressing knowledge about classes and properties in an ontology. It is a desirable modeling feature in multiple applications that simplifies the extension and reuse of ontologies. Nevertheless, allowing metamodeling without restrictions is problematic for several reasons, mainly due to undecidability issues. Practical languages, therefore, forbid classes to occur as instances of other classes or treat such occurrences as semantically different objects. Specifically, meta-querying in SPARQL under the Direct Semantic Entailment Regime (DSER) uses the latter approach, thereby effectively not supporting meta-queries. However, several extensions enabling different metamodeling features have been proposed over the last decade. This paper deals with the Metamodeling Semantics (MS) over OWL 2 QL and the Metamodeling Semantic Entailment Regime (MSER), as proposed in Lenzerini et al. (2015) and Lenzerini et al. (2020); Cima et al. (2017). A reduction from OWL 2 QL to Datalog for meta-querying was proposed in Cima et al. (2017). In this paper, we experiment with various logic programming tools that support Datalog querying to determine their suitability as back-ends to MSER query answering. These tools stem from different logic programming paradigms (Prolog, pure Datalog, Answer Set Programming, Hybrid Knowledge Bases). Our work shows that the Datalog approach to MSER querying is practical also for sizeable ontologies with limited resources (time and memory). This paper significantly extends Qureshi & Faber (2021) by a more detailed experimental analysis and more background. Under consideration in Theory and Practice of Logic Programming (TPLP).
Abstract (translated)
元建模是一种表达关于类和属性的知识的方法，应用于知识图谱。在多个应用中，元建模是一个理想的建模特征，可以简化知识图谱的扩展和重用。然而，无限制地允许元建模会存在问题，主要原因是不可判定性问题。因此，实用的语言禁止类作为其他类的实例出现，或者将这种现象视为语义上不同的对象。具体来说，在SPARQL的元查询 under Direct Semantic Entailment Regime (DSER) 下，元查询采用后者的方法，从而实质上不支持元查询。然而，在过去的十年里，已经提出了许多支持不同元建模功能的扩展。本文处理的是OWL 2 QL和元建模语义规则（MSR）中的元建模语义（MS）以及Cima等人（2017）提出的元建模语义规则。Cima等人（2017）提出了从OWL 2 QL到Datalog的减少方案，用于元查询。本文我们还研究了各种支持Datalog查询的逻辑编程工具，以确定它们作为MSER查询回答后端的可行性。这些工具源于不同的逻辑编程范式（Prolog，纯Datalog，答案集编程，混合知识数据库）。我们的工作表明，即使对于资源有限的大型知识图谱，元建模方法在MSER查询上也具有实用性。本文在《理论与实践逻辑编程》（TPLP）中大大扩展了Qureshi & Faber（2021）的内容，增加了更详细的实验分析和背景。
URL
https://arxiv.org/abs/2402.02978
