title: Creating mappings for ontologies in biomedicine: simple methods work.
abstract: Creating mappings between concepts in different ontologies is a critical step in facilitating data integration. In recent years, researchers have developed many elaborate algorithms that use graph structure, background knowledge, machine learning and other techniques to generate mappings between ontologies. We compared the performance of these advanced algorithms on creating mappings for biomedical ontologies with the performance of a simple mapping algorithm that relies on lexical matching. Our evaluation has shown that (1) most of the advanced algorithms are either not publicly available or do not scale to the size of biomedical ontologies today, and (2) for many biomedical ontologies, simple lexical matching methods outperform most of the advanced algorithms in both precision and recall. Our results have practical implications for biomedical researchers who need to create alignments for their ontologies.
authors.affiliation: Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA, USA.
authors.forename: Amir
authors.initials: A
authors.lastname: Ghazvinian
authors.forename: Natalya F
authors.initials: NF
authors.lastname: Noy
authors.forename: Mark A
authors.initials: MA
authors.lastname: Musen
mesh_terms: D000465:Algorithms; D018875:Vocabulary, Controlled