Bioinformatics Commons^™

Missing Lateral Relationships In Top‑Level Concepts Of An Ontology, Ling Zheng, Yan Chen, Hua Min, P. Lloyd Hildebrand, Hao Liu, Michael Halper, James Geller, Sherri De Coronado, Yehoshua Perl

Publications and Research

Background: Ontologies house various kinds of domain knowledge in formal structures, primarily in the form of concepts and the associative relationships between them. Ontologies have become integral components of many health information processing environments. Hence, quality assurance of the conceptual content of any ontology is critical. Relationships are foundational to the definition of concepts. Missing relationship errors (i.e., unintended omissions of important definitional relationships) can have a deleterious effect on the quality of an ontology. An abstraction network is a structure that overlays an ontology and provides an alternate, summarization view of its contents. One kind of abstraction network is …

Outlier Concepts Auditing Methodology For A Large Family Of Biomedical Ontologies, Ling Zheng, Hua Min, Yan Chen, Vipina Keloth, James Geller, Yehoshua Perl, George Hripcsak

Publications and Research

Background: Summarization networks are compact summaries of ontologies. The “Big Picture” view offered by summarization networks enables to identify sets of concepts that are more likely to have errors than control concepts. For ontologies that have outgoing lateral relationships, we have developed the "partial-area taxonomy" summarization network. Prior research has identified one kind of outlier concepts, concepts of small partials-areas within partial-area taxonomies. Previously we have shown that the small partial-area technique works successfully for four ontologies (or their hierarchies).

Methods: To improve the Quality Assurance (QA) scalability, a family-based QA framework, where one QA technique is potentially applicable to …