title: An analysis of FMA using structural self-bisimilarity.
abstract: As ontologies are mostly manually created, they tend to contain errors and inconsistencies. In this paper, we present an automated computational method to audit symmetric concepts in ontologies by leveraging self-bisimilarity and linguistic structure in the concept names. Two concepts A and B are symmetric if concept B can be obtained from concept A by replacing a single modifier such as "left" with its symmetric modifier such as "right." All possible local structural types for symmetric concept pairs are enumerated according to their local subsumption hierarchy, and the pairs are further classified into Non-Matches and Matches. To test the feasibility and validate the benefits of this method, we computed all the symmetric modifier pairs in the Foundational Model of Anatomy (FMA) and selected six of them for experimentation. 9893 Non-Matches and 221 abnormal Matches with potential errors were discovered by our algorithm. Manual evaluation by FMA domain experts on 176 selected Non-Matches and all the 221 abnormal Matches found 102 missing concepts and 40 misaligned concepts. Corrections for them have currently been implemented in the latest version of FMA. Our result demonstrates that self-bisimilarity can be a valuable method for ontology quality assurance, particularly in uncovering missing concepts and misaligned concepts. Our approach is computationally scalable and can be applied to other ontologies that are rich in symmetric concepts.
authors.affiliation: Division of Medical Informatics, Case Western Reserve University, Cleveland, OH, USA. lxl342@case.edu
authors.forename: Lingyun
authors.initials: L
authors.lastname: Luo
authors.forename: José L V
authors.initials: JL
authors.lastname: Mejino
authors.forename: Guo-Qiang
authors.initials: GQ
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D016247:Information Storage and Retrieval; D018875:Vocabulary, Controlled
references.citation: J Biomed Inform. 2009 Jun;42(3):413-25
references.pmid: 19285571
references.citation: J Biomed Inform. 2007 Oct;40(5):561-81
references.pmid: 17276736
references.citation: Artif Intell Med. 2007 Mar;39(3):217-25
references.pmid: 17254759
references.citation: Proc AMIA Symp. 2001;:57-61
references.pmid: 11825155
references.citation: J Biomed Inform. 2003 Dec;36(6):478-500
references.pmid: 14759820
references.citation: Int J Med Inform. 2002 Dec 4;67(1-3):85-95
references.pmid: 12460634
references.citation: AMIA Annu Symp Proc. 2012;2012:1060-9
references.pmid: 23304382
references.citation: J Biomed Inform. 2009 Jun;42(3):407-11
references.pmid: 19465342
references.citation: J Biomed Inform. 2009 Jun;42(3):440-51
references.pmid: 19303057
references.citation: AMIA Jt Summits Transl Sci Proc. 2013 Mar 18;2013:157-61
references.pmid: 24303256
references.citation: J Am Med Inform Assoc. 2006 Nov-Dec;13(6):676-90
references.pmid: 16929044
references.citation: Proc AMIA Symp. 2002;:61-5
references.pmid: 12463787
references.citation: Stud Health Technol Inform. 2010;160(Pt 2):1070-4
references.pmid: 20841848
references.citation: AMIA Annu Symp Proc. 2012;2012:643-52
references.pmid: 23304337
references.citation: Semant Web ISWC. 2010;6497:273-288
references.pmid: 25699294
references.citation: AMIA Annu Symp Proc. 2007 Oct 11;:851-5
references.pmid: 18693957
references.citation: J Biomed Inform. 2009 Jun;42(3):550-7
references.pmid: 19475727
references.citation: Pac Symp Biocomput. 2005;:91-102
references.pmid: 15759617
references.citation: AMIA Annu Symp Proc. 2010 Nov 13;2010:922-6
references.pmid: 21347113