LOGO: Logics for Ontologies

本体论通过提供术语词汇表以及对术语含义及其之间关系的正式和计算机可处理的描述来帮助人类和计算机应用程序进行通信。它们在下一代万维网（称为语义网）中扮演着重要角色，它们被用来描述Web资源的内容，目的是改善人类用户的搜索，并使计算机程序更容易利用Web上的大量信息。本体也被广泛用于定义医学、生物学和其他科学学科中使用的专业词汇。本体通常由人类专家开发，但即使对于专家来说，定义所有相关术语的工作也是困难和耗时的。因此，重要的是提供智能工具，支持本体设计师。出于这个原因，许多本体语言，包括OWL（用于语义Web本体的标准语言），都是基于逻辑的。这提供了语言含义的正式规范，并允许工具使用自动推理系统，例如，检查描述之间的相互作用不会导致逻辑矛盾。当本体被部署在应用中时，推理系统也是有用的，在应用中它们可以被使用，例如，本体在上述应用中的中心作用带来了对表达能力和推理支持的要求，这些要求超出了现有本体语言和推理系统的能力。例如，OWL不能表达一个人父亲的兄弟也是他的叔叔的事实，即使对于OWL，也没有实用的推理系统。此外，现有的推理系统往往有困难，处理非常大的本体，在许多现实的应用程序中需要。本提案中所述的研究旨在弥合需求和能力之间的鸿沟;其最终目标是开发逻辑和推理技术，这些技术将构成下一代本体语言和推理系统的基础。第一部分将关注现有的本体语言，以及它们所基于的逻辑。其目的是设计这些本体语言的主要扩展，以满足医学和语义Web等应用领域的表达需求。第二部分将重点关注现有本体语言和第一部分开发的扩展语言的实现技术。目标是开发高度优化的推理系统，能够支持大规模应用中本体的设计和部署。第三条链将集中在非常有表现力的本体语言上。这些语言是基于逻辑的，已知不可能建立可以解决任何问题的推理系统，例如，一个保证能检测出所有可能的矛盾的系统目的是开发推理系统，仍然能够有效地解决绝大多数问题，从使用本体在application.Finally，为了确保正在开发的逻辑，算法和推理系统确实满足应用程序的要求，他们将进行测试和评估，在本体设计师和开发人员的合作，基于本体的应用程序。

Ontologies help both humans and computer applications to communicate by providing a vocabulary of terms together with formal and computerprocessable descriptions of their meanings and the relationships between them. They play a major role in the next-generation World Wide Web (known as the Semantic Web), where they are used to describe the content of Web resources, with the aim of both Improving search for human users and making it easier for computer programs to exploit the vast range of information that is available on the Web. Ontologies are also widely used to define specialised vocabularies for use in medicine, biology and other scientific disciplines.Ontologies are usually developed by human experts, but even for experts the job of defining all the relevant terms is a difficult and time consuming one. It is therefore important to provide intelligent tools that support ontology designers. For this reason, many ontology languages, including OWL (the standard language used for Semantic Web ontologies), are based on logics, This provides a formal specification of the meaning of the language and allows tools to use automated reasoning systems, e.g., to check that Interactions between descriptions do not lead to logical contradictions. Reasoning systems are also useful when ontologies are deployed in applications, where they could be used, e.g., to determine which Web pages match a search request that uses terms defined In an ontology.The central role of ontologies in the above mentioned applications brings with it, however, requirements for expressive power and reasoning support which are beyond the capabilities of existing ontology languages and reasoning systems. For example, OWL cannot express the fact that the brother of a persons father is also their uncle, and even for OWL, no practical reasoning system is yet available. Moreover, existing reasoning systems often have difficulties dealing with the very large ontologies that are needed in many realistic applications. The research described in this proposal aims at bridging this gulf between requirements and capabilities; its ultimate goal is the development of logics and reasoning techniques that that will form the foundations of the next generation of ontology languages and reasoning systems.The research programme will be made up of three complementary strands. The first strand will focus on existing ontology languages, and the logics on which they are based. The aim will be to devise principaled extensions of these ontology languages that meet expressive requirements that have been identified in application areas such as medicine and the Semantic Web.The second strand will focus on implementation techniques for existing ontology languages and for extended languages developed in the first strand. The aim will be to develop highly optimised reasoning systems capable of supporting both the design and deployment of ontologies in large scale applications.The third strand will focus on very expressive ontology languages. These languages are based on logics where it is known to be impossible to build a reasoning system that can solve any problem, e.g., one that is guaranteed to detect all possible contradictions. The aim is to develop reasoning systems that will still be able to efficiently solve the vast majority of problems derived from the use of ontologies in applications.Finally, in order to ensure that the logics, algorithms and reasoning systems being developed really do meet application requirements, they will be tested and evaluated in cooperation with ontology designers and developers of ontology based applications.