Bridging the semantics gap between terminologies, ontologies, and information models.
SNOMED CT and other biomedical vocabularies provide semantic identifiers for all kinds of linguistic expressions, many of which cannot be considered terms in a strict sense. We analyzed such "non-terms" in SNOMED CT and concluded that many of them cannot be interpreted as directly referring to objects or processes, but rather to information entities. Discussing two approaches to represent information entities, viz. the OBO Information artifact ontology (IAO) and the HL7 v3 Reference Information Model (RIM), we propose an integrative solution for representing information entities in SNOMED CT, in a way that is still compatible with RIM and the IAO and uses moderately enhanced description logics.
Schulz
Stefan
S
Institute of Medical Biometry Medical Informatics, University Medical Center Freiburg, Germany. stschulz@uni-freiburg.de
Schober
Daniel
D
Daniel
Christel
C
Jaulent
Marie-Christine
MC
D016247:Information Storage and Retrieval / Q000379:methods; D012660:Semantics; D039061:Systematized Nomenclature of Medicine; D009626:Terminology as Topic; D018875:Vocabulary, Controlled