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一个用于为本体推导、可视化和探索抽象网络的统一软件框架。

A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies.

作者信息

Ochs Christopher, Geller James, Perl Yehoshua, Musen Mark A

机构信息

Computer Science Department, New Jersey Institute of Technology, Newark, NJ 07102, USA.

Computer Science Department, New Jersey Institute of Technology, Newark, NJ 07102, USA.

出版信息

J Biomed Inform. 2016 Aug;62:90-105. doi: 10.1016/j.jbi.2016.06.008. Epub 2016 Jun 23.

Abstract

Software tools play a critical role in the development and maintenance of biomedical ontologies. One important task that is difficult without software tools is ontology quality assurance. In previous work, we have introduced different kinds of abstraction networks to provide a theoretical foundation for ontology quality assurance tools. Abstraction networks summarize the structure and content of ontologies. One kind of abstraction network that we have used repeatedly to support ontology quality assurance is the partial-area taxonomy. It summarizes structurally and semantically similar concepts within an ontology. However, the use of partial-area taxonomies was ad hoc and not generalizable. In this paper, we describe the Ontology Abstraction Framework (OAF), a unified framework and software system for deriving, visualizing, and exploring partial-area taxonomy abstraction networks. The OAF includes support for various ontology representations (e.g., OWL and SNOMED CT's relational format). A Protégé plugin for deriving "live partial-area taxonomies" is demonstrated.

摘要

软件工具在生物医学本体的开发和维护中起着关键作用。没有软件工具,本体质量保证这一重要任务就会变得困难。在之前的工作中,我们引入了不同类型的抽象网络,为本体质量保证工具提供理论基础。抽象网络总结了本体的结构和内容。我们反复使用以支持本体质量保证的一种抽象网络是局部区域分类法。它在结构和语义上总结了本体中的相似概念。然而,局部区域分类法的使用是临时的,无法推广。在本文中,我们描述了本体抽象框架(OAF),这是一个用于推导、可视化和探索局部区域分类法抽象网络的统一框架和软件系统。OAF支持各种本体表示形式(例如,OWL和SNOMED CT的关系格式)。展示了一个用于推导“实时局部区域分类法”的Protégé插件。

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