Linked Life Data

15492037

Source:http://linkedlifedata.com/resource/pubmed/id/15492037

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2005-1-6
pubmed:abstractText
The Digital Anatomist Foundational Model of Anatomy (FMA) is a large semantic network of more than 100,000 terms that refer to the anatomical entities, which together with 1.6 million structural relationships symbolically represent the physical organization of the human body. Evaluation of such a large knowledge base by domain experts is challenging because of the sheer size of the resource and the need to evaluate not just classes but also relationships. To meet this challenge, the authors have developed a relation-centric query interface, called Emily, that is able to query the entire range of classes and relationships in the FMA, yet is simple to use by a domain expert. Formative evaluation of this interface considered the ability of Emily to formulate queries based on standard anatomy examination questions, as well as the processing speed of the query engine. Results show that Emily is able to express 90% of the examination questions submitted to it and that processing time is generally 1 second or less, but can be much longer for complex queries. These results suggest that Emily will be a very useful tool, not only for evaluating the FMA, but also for querying and evaluating other large semantic networks.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1067-5027
pubmed:author
pubmed:issnType
Print
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
35-46
pubmed:dateRevised
2011-8-1
pubmed:meshHeading
pubmed:articleTitle
Processes and problems in the formative evaluation of an interface to the Foundational Model of Anatomy knowledge base.
pubmed:affiliation
Structural Informatics Group, Department of Medical Education and Biomedical Informatics, Box 352350, Computer Science and Engineering, 634 Paul Allen Center, University of Washington, Seattle, WA 98195, USA. shapiro@cs.washington.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Evaluation Studies, Research Support, N.I.H., Extramural