NDLI: Quality assurance of the content of a large DL-based terminology using mixed lexical and semantic criteria: experience with SNOMED CT

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Quality assurance of the content of a large DL-based terminology using mixed lexical and semantic criteria: experience with SNOMED CT

Content Provider	ACM Digital Library
Author	Iannone, Luigi Stevens, Robert Rector, Alan
Abstract	SNOMED-CT is a large medical terminology based on description logic and mandated for use in the US, UK and several other countries. The hierarchies are known to contain many errors, but have so far proved difficult to analyse or quality assure. We present a series of methods and lessons learnt from experience in quality assuring a "module" of SNOMED for specific applications that we expect to generalize both to SNOMED as a whole and to other large ontologies. They feature a) dependence on domain exper-tise b) starting from classes selected for relevance to specific applications, c) tracing all errors to their root and verifying repairs by reclassification d) extraction of manageable-sized "modules"; e) mixed semantic and lexical criteria, and f) extensive use of scripting. They aim to reduce the cognitive load on experts by a) looking initially up-wards rather than downwards in the hierarchies, b) breaking up long lists of direct subclasses by introducing definitions for meaningful subcategories. Errors found range from simple mistakes to systematic errors in schemas.
Starting Page	57
Ending Page	64
Page Count	8
File Format	PDF
ISBN	9781450303965
DOI	10.1145/1999676.1999688
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-06-26
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Modularization Quality assurance Owl Description logics Ontologies
Content Type	Text
Resource Type	Article

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