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Mining Relation Reversals in the Evolution of SNOMED CT Using MapReduce

Relation reversals in ontological systems refer to such patterns as a path from concept A to concept B in one version becoming a path with the position of A and B switched in another version. We present a scalable approach, using cloud computing, to systematically extract all hierarchical relation r...

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Detalles Bibliográficos
Autores principales: Tao, Shiqiang, Cui, Licong, Zhu, Wei, Sun, Mengmeng, Bodenreider, Olivier, Zhang, Guo-Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525241/
https://www.ncbi.nlm.nih.gov/pubmed/26306232
Descripción
Sumario:Relation reversals in ontological systems refer to such patterns as a path from concept A to concept B in one version becoming a path with the position of A and B switched in another version. We present a scalable approach, using cloud computing, to systematically extract all hierarchical relation reversals among 8 SNOMED CT versions from 2009 to 2014. Taking advantage of our MapReduce algorithms for computing transitive closure and large-scale set operations, 48 reversals were found through 28 pairwise comparison of the 8 versions in 18 minutes using a 30-node local cloud, to completely cover all possible scenarios. Except for one, all such reversals occurred in three sub-hierarchies: Body Structure, Clinical Finding, and Procedure. Two (2) reversal pairs involved an uncoupling of the pair before the is-a coupling is reversed. Twelve (12) reversal pairs involved paths of length-two, and none (0) involved paths beyond length-two. Such reversals not only represent areas of potential need for additional modeling work, but also are important for identifying and handling cycles for comparative visualization of ontological evolution.