A family-based framework for supporting quality assurance of biomedical ontologies in BioPortal.

Zhe He, Christopher Ochs, Ankur Agrawal, Yehoshua Perl, Dimitris Zeginis, Konstantinos Tarabanis, Gai Elhanan, Michael Halper, Natasha Noy, James Geller

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


BioPortal contains over 300 ontologies, for which quality assurance (QA) is critical. Abstraction networks (ANs), compact summarizations of ontology structure and content, have been used in such QA efforts, typically in a "one-off" manner for a single ontology. Ontologies can be characterized-independently of knowledge-content focus-from a structural standpoint leading to the formulation of ontology families. A family is defined as a set of ontologies satisfying some overarching condition regarding their structural features. Seven such families, comprising 186 ontologies, are identified. To increase efficiency, a new family-based QA framework is introduced in which an automated, uniform AN derivation technique and accompanying semi-automated, uniform QA regimen are applicable to the ontologies of a given family. Specifically, across an entire family, the QA efforts exploit family-wide AN features in the characterization of sets of classes that are more likely to harbor errors. The approach is demonstrated on the Cancer Chemoprevention BioPortal ontology.

Original languageEnglish (US)
Pages (from-to)581-590
Number of pages10
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2013

All Science Journal Classification (ASJC) codes

  • General Medicine


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