OBJECTIVE: This paper investigates several methods for aligning Metathesaurus relationships with their counterparts in the UMLS Semantic Network. Unlike the categorization link defined between Metathesaurus concepts and Semantic Network types, no such correspondence exists between the relationships at these two levels of the UMLS. METHODS: The first approach attempts to elicit the semantics of Metathesaurus relationships through an examination of their relata at different levels: concept, high-level ancestors and semantic types. The second approach examines the frequency of association between a given Semantic Network relationship and the actual relationships observed in the Metathesaurus between the concepts categorized by these semantic types. RESULTS: A total of 139 relationships are present in the Metathesaurus. Using the methods described in this paper, 80 (58%) could be aligned with Semantic Network relationships. The remaining relationships are vocabulary internal, used, for example, for vocabulary management or to indicate strictly lexical relationships. The work reported here is a first step in the attempt to build a more comprehensive ontology of biomedical relationships.
OBJECTIVE: This paper investigates several methods for aligning Metathesaurus relationships with their counterparts in the UMLS Semantic Network. Unlike the categorization link defined between Metathesaurus concepts and Semantic Network types, no such correspondence exists between the relationships at these two levels of the UMLS. METHODS: The first approach attempts to elicit the semantics of Metathesaurus relationships through an examination of their relata at different levels: concept, high-level ancestors and semantic types. The second approach examines the frequency of association between a given Semantic Network relationship and the actual relationships observed in the Metathesaurus between the concepts categorized by these semantic types. RESULTS: A total of 139 relationships are present in the Metathesaurus. Using the methods described in this paper, 80 (58%) could be aligned with Semantic Network relationships. The remaining relationships are vocabulary internal, used, for example, for vocabulary management or to indicate strictly lexical relationships. The work reported here is a first step in the attempt to build a more comprehensive ontology of biomedical relationships.
Authors: Barry Smith; Werner Ceusters; Bert Klagges; Jacob Köhler; Anand Kumar; Jane Lomax; Chris Mungall; Fabian Neuhaus; Alan L Rector; Cornelius Rosse Journal: Genome Biol Date: 2005-04-28 Impact factor: 13.583