Performance evaluation is increasingly relevant for Web Ontology Language (OWL) reasoners, due to the expanding availability of knowledge corpuses on the Web, the growing variety of applications, and the rise to prominence of mobile and pervasive computing. Motivated mainly by the difficulty of comparing reasoning engines in the Semantic Web of Things (SWoT), this paper introduces evOWLuator, a novel approach and a multiplatform framework devised to be both flexible and expandable. It features integration of traditional and mobile/embedded engines as well as ontology dataset management, reasoning test execution, and report generation. A case study consisting of an experimental setting for time, memory peak and energy footprint evaluation with eight reasoners and four different platforms allows showcasing usage and validating features and usability of the tool.

由于 Web 上知识语料库的可用性不断扩大，应用程序的种类不断增加，以及移动和普适计算的兴起，性能评估与 Web 本体语言 (OWL) 推理器越来越相关。主要受语义网 (SWoT) 中的推理引擎比较困难的启发，本文介绍了evOWLuator，一种新颖的方法和多平台框架，旨在灵活和可扩展。它集成了传统和移动/嵌入式引擎以及本体数据集管理、推理测试执行和报告生成。案例研究包括时间、内存峰值和能量足迹评估的实验设置，带有八个推理器和四个不同的平台，可以展示工具的使用和验证功能和可用性。