Utilizing a structural meta-ontology for family-based quality assurance of the BioPortal ontologies.
Utilizing a structural meta-ontology for family-based quality assurance of the BioPortal ontologies.
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DOI：
10.1016/j.jbi.2016.03.007
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发表时间：
2016-06
影响因子：
4.5
通讯作者：
Musen MA
中科院分区：
文献类型：
--
作者：
Ochs C;He Z;Zheng L;Geller J;Perl Y;Hripcsak G;Musen MA
抽象网络是本体结构和内容的紧凑总结。在之前的研究中，我们表明抽象网络支持生物医学本体的质量保证（QA）。然而，抽象网络及其相关的 QA 方法的开发是一个劳动密集型的过程，以前一次只能适用于一个本体。为了提高基于抽象网络的 QA 方法的效率，我们引入了一个 QA 框架，该框架使用统一的抽象网络推导技术和 QA 方法，适用于结构相似的本体的整个系列。为了使基于族的框架取得成功，有必要开发一种将本体分类为结构相似的族的方法。我们现在描述一种结构元本体，它根据本体建模中常用的某些结构特征（例如对象属性）对本体进行分类，并且这些特征对于抽象网络推导很重要。结构元本体的每一类都代表具有相同结构特征的本体家族，表明哪些类型的抽象网络和质量保证方法可能适用于该家族中的所有本体。我们导出了 81 个家族的集合，对应于结构元本体的类别，从而实现了灵活、简化的基于家族的 QA 方法，为本体分类提供了多种选择。分析了 NCBO BioPortal 的 373 个本体的结构，每个本体被分为由结构元本体建模的多个家族。
An Abstraction Network is a compact summary of an ontology’s structure and content. In previous research, we showed that Abstraction Networks support quality assurance (QA) of biomedical ontologies. The development of an Abstraction Network and its associated QA methodologies, however, is a labor-intensive process that previously was applicable only to one ontology at a time. To improve the efficiency of the Abstraction-Network–based QA methodology, we introduced a QA framework that uses uniform Abstraction Network derivation techniques and QA methodologies that are applicable to whole families of structurally similar ontologies. For the family-based framework to be successful, it is necessary to develop a method for classifying ontologies into structurally similar families. We now describe a structural meta-ontology that classifies ontologies according to certain structural features that are commonly used in the modeling of ontologies (e.g., object properties) and that are important for Abstraction Network derivation. Each class of the structural meta-ontology represents a family of ontologies with identical structural features, indicating which types of Abstraction Networks and QA methodologies are potentially applicable to all of the ontologies in the family. We derive a collection of 81 families, corresponding to classes of the structural meta-ontology, that enable a flexible, streamlined family-based QA methodology, offering multiple choices for classifying an ontology. The structure of 373 ontologies from the NCBO BioPortal is analyzed and each ontology is classified into multiple families modeled by the structural meta-ontology.