Summarizing and visualizing structural changes during the evolution of biomedical ontologies using a Diff Abstraction Network

Document Type

Article

Publication Date

8-1-2015

Abstract

Biomedical ontologies are a critical component in biomedical research and practice. As an ontology evolves, its structure and content change in response to additions, deletions and updates. When editing a biomedical ontology, small local updates may affect large portions of the ontology, leading to unintended and potentially erroneous changes. Such unwanted side effects often go unnoticed since biomedical ontologies are large and complex knowledge structures. Abstraction networks, which provide compact summaries of an ontology's content and structure, have been used to uncover structural irregularities, inconsistencies and errors in ontologies. In this paper, we introduce Diff Abstraction Networks ("Diff AbNs"), compact networks that summarize and visualize global structural changes due to ontology editing operations that result in a new ontology release. A Diff AbN can be used to support curators in identifying unintended and unwanted ontology changes. The derivation of two Diff AbNs, the Diff Area Taxonomy and the Diff Partial-area Taxonomy, is explained and Diff Partial-area Taxonomies are derived and analyzed for the Ontology of Clinical Research, Sleep Domain Ontology, and eagle-i Research Resource Ontology. Diff Taxonomy usage for identifying unintended erroneous consequences of quality assurance and ontology merging are demonstrated.

Identifier

84938574995 (Scopus)

Publication Title

Journal of Biomedical Informatics

External Full Text Location

https://doi.org/10.1016/j.jbi.2015.05.018

ISSN

15320464

PubMed ID

26048076

First Page

127

Last Page

144

Volume

56

Grant

R01CA190779

Fund Ref

National Cancer Institute

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