Ontology Recommender Web service

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To automatically recommend an ontology to use for semantic annotations

Background

As the use of ontologies for annotation of biomedical datasets rises, a common question researchers face is that of identifying which ontologies are relevant to annotate their datasets. The number and variety of biomedical ontologies is now quite large and it is cumbersome for a scientist to figure out which ontology to (re)use in their annotation tasks. NCBO develops an ontology recommender service, which informs the user of the most appropriate ontologies relevant for their given dataset. The recommender service uses a semantic annotation based approach and scores the ontologies according to those annotations. The recommender service uses the Annotator Web service . The prototype service can recommend ontologies from UMLS and the NCBO BioPortal.

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NCBO Recommender Web Service workflow

Please try the Ontology Recommender: http://bioportal.bioontology.org/recommender

Contacts

Documentation

Service Signature

  • Optional arguments:
    • format=[simpleText/text/xml] – the output format (default: xml)
    • ontologyids=<ontologyid>,<ontologyid>… - limits the recommendations to specific ontologies, identified by virtual IDs (default: all ontologies)

References

  • Please refer to:
    • Jonquet C, Musen MA, Shah NH. Building a biomedical ontology recommender web service. J Biomed Semantics. 2010 Jun 22;1 Suppl 1:S1. PubMed PMID: 20626921; PubMed Central PMCID: PMC2903720.
    • Clement Jonquet, Nigam H. Shah, Mark A. Musen, Prototyping a Biomedical Ontology Recommender Service, Bio-Ontologies: Knowledge in Biology, SIG, ISMBECCB 2009, pp. 65-68, Stockholm, Sweden, July 2009. Stanford BMIR Publications SIG's web site click on "programme booklet"

Versions (prototypes & releases)

Evaluation

The original datasets used for evaluating the Recommender 1.1, as well as the recommendations generated are available here: http://obs.bioontology.org/recommender/results/

Collaboration & Acknowledgment

  • The user interface for the recommender serice UI prototype is designed & developed by NCBO members from University of Victoria
  • We also thank Helen Parkinson (European Biomedical Institute), Stephen Granite (Johns Hopkins University) and Wei-Nchih Lee (Stanford University) for the help in the Recommender (version 1.1) evaluation.