层次控制词汇与OWL本体的整合:来自分子相互作用领域的案例研究

Melissa J. Davis, A. Newman, I. Khan, J. Hunter, M. Ragan
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引用次数: 4

摘要

在标准化生物领域内的术语方面的许多努力已经导致构建捕获领域知识的分层控制词汇表。词汇表,如PSI-MI词汇表,以OBO(开放生物医学本体)格式捕获深度和广泛的领域知识。然而,分层词汇表,如在OBO中表示的PSI-MI,只表示术语之间的简单父子关系。相比之下,使用Web本体语言(OWL)(如BioPax)构建的本体定义了术语之间更丰富的关系类型。OWL提供了一种语义丰富的结构化语言,用于表达实体和属性的类和子类、它们之间的关系以及可用于通过语义推理提取新信息的特定于领域的规则或公理。为了充分利用特定于领域的受控词汇表中固有的领域知识,需要将它们表示为OWL-DL本体,而不是以OBO等格式表示。在本文中,我们描述了一种将OBO词汇表转换为OWL和以OWL- rdf三元组表示的类实例的方法。这种方法保留了领域知识的层次结构,同时也使推理引擎可以使用底层的父子关系。与现有的方法相比,这种方法也有明显的优势,现有的方法将来自外部受控词汇表的术语合并为字面量,剥离了与其在层次结构中的位置相关的上下文。通过保留此上下文,我们使机器能够对OBO控制词汇表中捕获的有序领域知识进行推理
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrating Hierarchical Controlled Vocabularies With OWL Ontology: A Case Study from the Domain of Molecular Interactions
Many efforts at standardising terminologies within the biological domain have resulted in the construction of hierarchical controlled vocabularies that capture domain knowledge. Vocabularies, such as the PSI-MI vocabulary, capture both deep and extensive domain knowledge, in the OBO (Open Biomedical Ontologies) format. However hierarchical vocabularies, such as PSI-MI which are represented in OBO, only represent simple parent-child relationships between terms. By contrast, ontologies constructed using the Web Ontology Language (OWL), such as BioPax, define many richer types of relationships between terms. OWL provides a semantically rich structured language for expressing classes and sub-classes of entities and properties, relationships between them and domain-specific rules or axioms that can be applied to extract new information through semantic inferencing. In order to fully exploit the domain knowledge inherent in domain-specific controlled vocabularies, they need to be represented as OWL-DL ontologies, rather than in formats such as OBO. In this paper, we describe a method for converting OBO vocabularies into OWL and class instances represented as OWL-RDF triples. This approach preserves the hierarchical arrangement of the domain knowledge whilst also making the underlying parent-child relationships available to inferencing engines. This approach also has clear advantages over existing methods which incorporate terms from external controlled vocabularies as literals stripped of the context associated with their place in the hierarchy. By preserving this context, we enable machine inferencing over the ordered domain knowledge captured in OBO controlled vocabularies
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