Auditing associative relations across two knowledge sources.

OBJECTIVES: This paper proposes a novel semantic method for auditing associative relations in biomedical terminologies. We tested our methodology on two Unified Medical Language System (UMLS) knowledge sources. METHODS: We use the UMLS semantic groups as high-level representations of the domain and range of relationships in the Metathesaurus and in the Semantic Network. A mapping created between Metathesaurus relationships and Semantic Network relationships forms the basis for comparing the signatures of a given Metathesaurus relationship to the signatures of the semantic relationship to which it is mapped. The consistency of Metathesaurus relations is studied for each relationship. RESULTS: Of the 177 associative relationships in the Metathesaurus, 84 (48%) exhibit a high-degree of consistency with the corresponding Semantic Network relationships. Overall, 63% of the 1.8 M associative relations in the Metathesaurus are consistent with relations in the Semantic Network. CONCLUSION: The semantics of associative relationships in biomedical terminologies should be defined explicitly by their developers. The Semantic Network would benefit from being extended with new relationships and with new relations for some existing relationships. The UMLS editing environment could take advantage of the correspondence established between relationships in the Metathesaurus and the Semantic Network. Finally, the auditing method also yielded useful information for refining the mapping of associative relationships between the two sources.

Enhancing biomedical ontologies through alignment of semantic relationships: exploratory approaches.

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.

Actions in health care organizations: an ontological analysis.

In order to ensure that the information and knowledge needed for the management of healthcare is appropriately shared, human behavior within health care organizations (HCOs) needs to be carefully analyzed. Hence, guidelines, protocols, and messaging standards must be combined with models of resources and processes of patient care that are based on a sound ontology of organizations. This requires a general theory of the ontology of social institutions. Among the many groups attempting to develop efficient ways of sharing information across healthcare systems and organizations is Health Level 7 (HL7). Here I address the question whether HL7 reflects a sound analysis of behavior within HCOs on the basis of a sound ontology of organizations. I then apply ontological principles designed to show how the Reference Information Model (RIM) might be modified in such a way as to support efficient communication of medical information within and between healthcare organizations.