Alignment of the UMLS semantic network with BioTop: methodology and assessment.
BACKGROUND
For many years, the Unified Medical Language System (UMLS) semantic network (SN) has been used as an upper-level semantic framework for the categorization of terms from terminological resources in biomedicine. BioTop has recently been developed as an upper-level ontology for the biomedical domain. In contrast to the SN, it is founded upon strict ontological principles, using OWL DL as a formal representation language, which has become standard in the semantic Web. In order to make logic-based reasoning available for the resources annotated or categorized with the SN, a mapping ontology was developed aligning the SN with BioTop.


METHODS
The theoretical foundations and the practical realization of the alignment are being described, with a focus on the design decisions taken, the problems encountered and the adaptations of BioTop that became necessary. For evaluation purposes, UMLS concept pairs obtained from MEDLINE abstracts by a named entity recognition system were tested for possible semantic relationships. Furthermore, all semantic-type combinations that occur in the UMLS Metathesaurus were checked for satisfiability.


RESULTS
The effort-intensive alignment process required major design changes and enhancements of BioTop and brought up several design errors that could be fixed. A comparison between a human curator and the ontology yielded only a low agreement. Ontology reasoning was also used to successfully identify 133 inconsistent semantic-type combinations.


BACKGROUND
BioTop, the OWL DL representation of the UMLS SN, and the mapping ontology are available at http://www.purl.org/biotop/.
Schulz
Stefan
S
Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany. stschulz@uni-freiburg.de
Beisswanger
Elena
E
van den Hoek
László
L
Bodenreider
Olivier
O
van Mulligen
Erik M
EM
D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D016247:Information Storage and Retrieval / Q000379:methods*; D010363:Pattern Recognition, Automated; D012660:Semantics; D017432:Unified Medical Language System / Q000592:standards*; D018875:Vocabulary, Controlled