OWL 有哪些用例？
我读过OWL - Web Ontology Language（只有几页），但是什么是真正的-world 用例/它的实现？
I've read about OWL - Web Ontology Language (few pages only), but what are some real-world use cases/implementations for it?
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有大量的用例。网络本体语言是一种用于形式化本体的语言，具有在网络上使用的特定视图。因此，有两种方法可以解释您的问题：本体的用例是什么以及 OWL（具体来说是语言）的用例是什么。依次解决每个问题：
本体是领域或概念化的可计算规范：它们是世界的可计算模型。因此，它们用于例如数据集成（如果数据被标记为本体类型作为元数据并且有足够的指定公理，则机器可以计算例如两个数据是否引用相同的事物/概念并且应该组合等...）或分面搜索和基于描述逻辑的查询。
OWL 语言的用例是，它允许本体通过使用类、公理等的 URI 存在于网络上（OWL 是语义网络工具堆栈的一部分）......还有许多其他本体语言，例如 OBO ，例如，它不允许您这样做。如果您想知道为什么这是一件好事，请考虑开放链接数据等。
There are a large number of use cases. The web ontology language is a language for formalising ontologies, with a particular view for use on the web. As such there are two ways of interpreting your question: what are the use cases for ontologies and what is the use case for OWL (the language specifically). Tackling each in turn:
Ontologies are computable specifications of a domain or a conceptualisation: they are computable models of the world. As such, they are used for, for example, data integration (if data is labeled with an ontological type as metadata and there are enough specifying axioms, a machine can compute whether, for example, two pieces of data refer to the same thing/concept and should be combined etc...) or faceted searching and Description Logic based querying.
The use case for OWL the language is, that it allows ontologies to live on the web (OWL is part of the semantic web tool stack) by using URIs for classes, axioms etc....there are many other ontology languages such as OBO, for example, which do not allow you to do this. If you are wondering why that is a good thing, think about open linked data etc.
现实世界的一个很好的例子是将“好的”（经过深思熟虑和定义的）本体与自然语言处理（NLP）等技术相结合。这将有助于教导 NLP 将自由文本或半结构化文本分组和分类为更有用的内容。
GATE 等技术可以利用自然语言甚至创建 OWL。查看这篇文章 （以及一般的博客）了解一些关于本体/分类概念的想法。
A good real world example would be combining a "good" (well thought out and defined) ontology with a technology like Natural Language Processing (NLP). This would aid in teaching the NLP to group and categorize free text or semi-structured text into something a lot more usable.
Technologies such as GATE can utilize and even create OWL from natural language. Check out this article (and blog in general) for some ideas on where you could go with the ontology/taxonomy concepts.
一个好的用例是使数据更具可重用性和可重用性。最初，它使组织能够以可跨领域重用的方式对其数据进行本土化，并且在人们不同意本土化模型的情况下，它提供了在特定领域的上下文中重新利用该数据的机制。 RDF 和 SWRL 的一定程度也是如此，只是水平略有不同。
A good usecase is making data more reusable and repurposeful. Initially itenables organisations to homegenised their data in a manner that is reusable across domains and in situations where people don't agree on a homegenised model, it provides mechanisms to repurpose that data in a specific domain's context. This is also true to an extent of RDFs and SWRL, at slightly different levels.