Abstract
Ontology engineering (OE) in large projects poses a number of challenges arising from the heterogeneous backgrounds of the various stakeholders, domain experts, and their complex interactions with ontology designers. This multi-party interaction often creates systematic ambiguities and biases from the elicitation of ontology requirements, which directly affect the design, evaluation and may jeopardise the target reuse. Meanwhile, current OE methodologies strongly rely on manual activities (e.g., interviews, discussion pages). After collecting evidence on the most crucial OE activities, we introduce OntoChat, a framework for conversational ontology engineering that supports requirement elicitation, analysis, and testing. By interacting with a conversational agent, users can steer the creation of user stories and the extraction of competency questions, while receiving computational support to analyse the overall requirements and test early versions of the resulting ontologies. We evaluate OntoChat by replicating the engineering of the Music Meta Ontology, and collecting preliminary metrics on the effectiveness of each component from users. We release all code at this https URL.
Abstract (translated)
大项目中的本体工程(OE)面临着来自各个利益相关者、专家和它们与本体设计者复杂互动所带来的挑战。这种多方互动通常会导致从提炼本体需求的过程中产生的系统歧义和偏见，这直接影响设计、评估，甚至可能危及目标重用。同时，当前的OE方法论在很大程度上依赖于手动活动（例如，访谈、讨论页面）。在收集有关最关键OE活动的证据后，我们介绍了OntoChat，一个支持对话本体工程需求抽取、分析和测试的框架。通过与交互式代理交互，用户可以引导创建用户故事和提取能力问题，同时获得计算机支持以分析总体要求并测试初步版本的 resulting 本体。我们通过复制音乐元本体的工程来评估OntoChat，并从用户那里收集关于每个组件有效性的初步度量。我们在这个链接上发布所有代码。
URL
https://arxiv.org/abs/2403.05921
