Using the abstraction network in complement to description logics for quality assurance in biomedical terminologies - a case study in SNOMED CT.

Abstract

OBJECTIVES: To investigate errors identified in SNOMED CT by human reviewers with help from the Abstraction Network methodology and examine why they had escaped detection by the Description Logic (DL) classifier. Case study; Two examples of errors are presented in detail (one missing IS-A relation and one duplicate concept). After correction, SNOMED CT is reclassified to ensure that no new inconsistency was introduced. CONCLUSIONS: DL-based auditing techniques built in terminology development environments ensure the logical consistency of the terminology. However, complementary approaches are needed for identifying and addressing other types of errors.