ArticleJournal of biomedical informatics2016
Utilizing a structural meta-ontology for family-based quality assurance of the BioPortal ontologies.
Article in Journal of biomedical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Missing lateral relationships in top-level concepts of an ontology.BMC medical informatics and decision making · 2020Article
- Outlier concepts auditing methodology for a large family of biomedical ontologies.BMC medical informatics and decision making · 2020Article
- Detecting missing IS-A relations in the NCI Thesaurus using an enhanced hybrid approach.BMC medical informatics and decision making · 2020Article
- Complex overlapping concepts: An effective auditing methodology for families of similarly structured BioPortal ontologies.Journal of biomedical informatics · 2018Article
- Assessing the practice of biomedical ontology evaluation: Gaps and opportunities.Journal of biomedical informatics · 2018Review
- OWL-NETS: Transforming OWL Representations for Improved Network Inference.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2018Article
- Quality assurance of chemical ingredient classification for the National Drug File - Reference Terminology.Journal of biomedical informatics · 2017Article
- An empirical analysis of ontology reuse in BioPortal.Journal of biomedical informatics · 2017Article
- From SNOMED CT to Uberon: Transferability of evaluation methodology between similarly structured ontologies.Artificial intelligence in medicine · 2017Article
- Taxonomy-Based Approaches to Quality Assurance of Ontologies.Journal of healthcare engineering · 2017Article
- Introducing the Big Knowledge to Use (BK2U) challenge.Annals of the New York Academy of Sciences · 2017Review
- A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies.Journal of biomedical informatics · 2016Article
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Authors and funding
7 authors.
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Abstract
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.
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