Identification of errors in the IEDB using ontologies

Abstract

The Immune Epitope Database (IEDB) is a free online resource that has manually curated over 18 500 references from the scientific literature. Our database presents experimental data relating to the recognition of immune epitopes by the adaptive immune system in a structured, searchable manner. In order to be consistent and accurate in our data representation across many different journals, authors and curators, we have implemented several quality control measures, such as curation rules, controlled vocabularies and links to external ontologies and other resources. Ontologies and other resources have greatly benefited the IEDB through improved search interfaces, easier curation practices, interoperability between the IEDB and other databases and the identification of errors within our dataset. Here, we will elaborate on how ontology mapping and usage can be used to find and correct errors in a manually curated database.