The Neighborhood Auditing Tool for the UMLS and its Source Terminologies

 
 
ABSTRACT:
The UMLS's integration of more than 100 source vocabularies makes it susceptible to errors.  Furthermore, its size and complexity can make it very difficult to locate such errors.  A software tool, called the Neighborhood Auditing Tool (NAT), that facilitates UMLS auditing is presented.  The NAT supports "neighborhood-based" auditing, where, at any given time, an auditor concentrates on a single focus concept and one of a variety of neighborhoods of its closely related concepts.  The NAT can be seen as a special browser for the complex structure of the UMLS's hierarchies.  Typical diagrammatic displays of concept networks have a number of shortcomings, so the NAT utilizes a hybrid diagram/text interface that features stylized neighborhood views which retain some of the best features of both the diagrammatic layouts and text windows while avoiding the shortcomings.  The NAT allows an auditor to display knowledge from both the Metathesaurus (concept) level and the Semantic Network (semantic type) level.  Various additional features of the NAT that support the auditing process are described.  The usefulness of the NAT is demonstrated through a group of case studies.  Its impact is tested with a study involving a select group of auditors.
 
BIO:
Dr. James Geller received an Electrical Engineering Diploma from the Technical University, Vienna, Austria, in 1979, and the MS Degree (1984) and Ph.D. degree (1988) in Computer Science from the State University of New York at Buffalo.  Dr. Geller joined the Computer Science Department of the New Jersey Institute of Technology (NJIT) in 1988. He was granted tenure and promoted to associate professor in 1993. Subsequently he was promoted to full professor in 2000.  Dr. Geller has authored and co-authored about forty journal papers and over fifty conference papers. These papers are in a number of areas, including Knowledge Representation, the Semantic Web, Semantic Modeling in Object-Oriented Databases, Web Mining, Medical Informatics, Medical Vocabularies, and Auditing of Ontologies and Medical Terminologies.

 


10/20/2010