title: Topological analysis of large-scale biomedical terminology structures.
abstract: OBJECTIVE
  To characterize global structural features of large-scale biomedical terminologies using currently emerging statistical approaches.
  
  
  METHODS
  Given rapid growth of terminologies, this research was designed to address scalability. We selected 16 terminologies covering a variety of domains from the UMLS Metathesaurus, a collection of terminological systems. Each was modeled as a network in which nodes were atomic concepts and links were relationships asserted by the source vocabulary. For comparison against each terminology we created three random networks of equivalent size and density.
  
  
  METHODS
  Average node degree, node degree distribution, clustering coefficient, average path length.
  
  
  RESULTS
  Eight of 16 terminologies exhibited the small-world characteristics of a short average path length and strong local clustering. An overlapping subset of nine exhibited a power law distribution in node degrees, indicative of a scale-free architecture. We attribute these features to specific design constraints. Constraints on node connectivity, common in more synthetic classification systems, localize the effects of changes and deletions. In contrast, small-world and scale-free features, common in comprehensive medical terminologies, promote flexible navigation and less restrictive organic-like growth.
  
  
  CONCLUSIONS
  While thought of as synthetic, grid-like structures, some controlled terminologies are structurally indistinguishable from natural language networks. This paradoxical result suggests that terminology structure is shaped not only by formal logic-based semantics, but by rules analogous to those that govern social networks and biological systems. Graph theoretic modeling shows early promise as a framework for describing terminology structure. Deeper understanding of these techniques may inform the development of scalable terminologies and ontologies.
authors: Department of Biomedical Informatics, Columbia University, Vanderbilt Clinic, 622 West 168th Street, New York, NY 10032, USA.
authors: Michael E
authors: ME
authors: Bales
authors: Yves A
authors: YA
authors: Lussier
authors: Stephen B
authors: SB
authors: Johnson
mesh_terms: D017432:Unified Medical Language System; D018875:Vocabulary, Controlled
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