Visual Justifications for Ontologies

本体论是一种高效地对数据进行推理的方法。本体在包括语义网、医学和法律在内的一系列应用中越来越普遍。本体论的开发和维护是需要逻辑推理和符号符号知识的熟练任务。然而，每个本体的各种各样的利益相关者可能不具备有效执行本体工程所需的技能集。鉴于使用本体论的关键系统，最重要的是本体论准确地编码预期的信息。包含错误的本体被称为不连贯的本体，由本体工程师进行调试或修复。现存的本体论推理者为这种不连贯提供了理由。然而，解释理由是一项不平凡和困难的任务。即使工程师了解本体论的领域，例如医学，以及用来表示理由的符号符号，他们仍然可能难以调试本体论。在不无意地移除预期行为的情况下调试本体尤其困难。这个项目将使用概念图来可视化理由，以减轻本体工程师的负担。使用概念图将有助于理解问题并建议对本体进行适当的修复。该项目将提供一些不同的本体论常见错误的可视化，并从经验上测试每个错误的有效性。通过这一过程，项目团队将能够制定有效的视觉理由。使用由项目合作伙伴(一家诺基亚公司)提供的数据隐私本体的真实世界示例，然后将对照同等的符号和自然语言理由来测试视觉理由。

Ontologies are a way of reasoning about data in an efficient manner. Ontologies are increasingly prevalent in a range of applications, including the Semantic Web, medicine and law. The development and maintenance of ontologies are skilled tasks requiring knowledge of logical reasoning and symbolic notations. However, the wide variety of stakeholders for each ontology may not have the necessary skill set to perform ontology engineering effectively. Given the critical systems in which ontologies are used, it is of paramount importance that the ontologies encode exactly the information intended. Ontologies containing errors, called incoherent ontologies, undergo debugging or repair by an ontology engineer. Extant ontology reasoners provide a justification for the incoherence. However, interpreting the justification is a non-trivial and difficult task. Even if the engineer understands the domain of the ontology, for example medicine, and the symbolic notation in which the justification is represented, they could still struggle to debug the ontology. It is especially difficult to debug the ontology without unintentionally removing intended behaviour. This project will use concept diagrams to visualise justifications to reduce the burden on the ontology engineer. Using concept diagrams will help both the understanding of the problem and suggest appropriate repairs to the ontology. The project will provide a number of different visualisations of common bugs in ontologies and empirically test the effectiveness of each. Through this process, the project team will be able to develop effective visual justifications. Using real-world examples of ontologies for data privacy supplied by the project partner HERE (a Nokia company) the visual justifications will then be tested against equivalent symbolic and natural language justifications.