NCBO Resource Index: Ontology-Based Search and Mining of Biomedical Resources

Clement Jonquet; Paea LePendu; Sean Falconer; Adrien Coulet; Natalya F. Noy; Mark A. Musen; Nigam H. Shah

lirmm-00622155, version 1

NCBO Resource Index: Ontology-Based Search and Mining of Biomedical Resources

Clement Jonquet ( Author to contact preferably , ) ^1, 2, Paea LePendu ¹, Sean Falconer ¹, Adrien Coulet ^1, 3, Natalya F. Noy ¹, Mark A. Musen ¹, Nigam H. Shah ¹

Journal of Journal of Web Semantics 9, 3 (2011) 316-324

Abstract: The volume of publicly available data in biomedicine is constantly increasing. However, these data are stored in different formats and on different platforms. Integrating these data will enable us to facilitate the pace of medical discoveries by providing scientists with a unified view of this diverse information. Under the auspices of the National Center for Biomedical Ontology (NCBO), we have developed the Resource Index--a growing, large-scale ontology-based index of more than twenty heterogeneous biomedical resources. The resources come from a variety of repositories maintained by organizations from around the world. We use a set of over 200 publicly available ontologies contributed by researchers in various domains to annotate the elements in these resources. We use the semantics that the ontologies encode, such as different properties of classes, the class hierarchies, and the mappings between ontologies, in order to improve the search experience for the Resource Index user. Our user interface enables scientists to search the multiple resources quickly and efficiently using domain terms, without even being aware that there is semantics "under the hood."

1: Stanford Center for BioMedical Informatics Research (BMIR)
Stanford University
2: Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM)
CNRS : UMR5506 – Université Montpellier II - Sciences et techniques
3: ORPAILLEUR (INRIA Lorraine - LORIA)
INRIA – CNRS : UMR7503 – Université Henri Poincaré - Nancy I – Université Nancy II – Institut National Polytechnique de Lorraine (INPL)

lirmm-00622155, version 1
http://hal-lirmm.ccsd.cnrs.fr/lirmm-00622155
oai:hal-lirmm.ccsd.cnrs.fr:lirmm-00622155
From: Clement Jonquet <>
Submitted on: Monday, 12 September 2011 09:59:49
Updated on: Monday, 11 March 2013 14:56:38

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DOI: 10.1016/j.websem.2011.06.005

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%% lirmm-00622155, version 1
%% http://hal-lirmm.ccsd.cnrs.fr/lirmm-00622155
@article{jonquet:lirmm-00622155,
    hal_id = {lirmm-00622155},
    url = {http://hal-lirmm.ccsd.cnrs.fr/lirmm-00622155},
    title = {{NCBO Resource Index: Ontology-Based Search and Mining of Biomedical Resources}},
    author = {Jonquet, Clement and LePendu, Paea and Falconer, Sean and Coulet, Adrien and Noy, Natalya F. and Musen, Mark A. and Shah, Nigam H.},
    abstract = {{The volume of publicly available data in biomedicine is constantly increasing. However, these data are stored in different formats and on different platforms. Integrating these data will enable us to facilitate the pace of medical discoveries by providing scientists with a unified view of this diverse information. Under the auspices of the National Center for Biomedical Ontology (NCBO), we have developed the Resource Index--a growing, large-scale ontology-based index of more than twenty heterogeneous biomedical resources. The resources come from a variety of repositories maintained by organizations from around the world. We use a set of over 200 publicly available ontologies contributed by researchers in various domains to annotate the elements in these resources. We use the semantics that the ontologies encode, such as different properties of classes, the class hierarchies, and the mappings between ontologies, in order to improve the search experience for the Resource Index user. Our user interface enables scientists to search the multiple resources quickly and efficiently using domain terms, without even being aware that there is semantics "under the hood."}},
    keywords = {Semantic Web, ontology-based indexing, semantic annotation, data integration, information mining, information retrieval, biomedical data, biomedical ontologies},
    language = {English},
    affiliation = {Stanford Center for BioMedical Informatics Research - BMIR , Laboratoire d'Informatique de Robotique et de Micro{\'e}lectronique de Montpellier - LIRMM , ORPAILLEUR - INRIA Lorraine - LORIA},
    publisher = {Elsevier},
    pages = {316-324},
    journal = {Journal of Journal of Web Semantics},
    volume = {9},
    number = {3 },
    note = {NIH Projet NCBO },
    audience = {international },
    doi = {10.1016/j.websem.2011.06.005 },
    year = {2011},
    month = Sep,
    pdf = {http://hal-lirmm.ccsd.cnrs.fr/lirmm-00622155/PDF/Article-JWS11-ncbo.pdf},
}

%F lirmm-00622155, version 1
%0 Journal Article
%U http://hal-lirmm.ccsd.cnrs.fr/lirmm-00622155
%T NCBO Resource Index: Ontology-Based Search and Mining of Biomedical Resources
%A Jonquet, Clement
%A LePendu, Paea
%A Falconer, Sean
%A Coulet, Adrien
%A Noy, Natalya F.
%A Musen, Mark A.
%A Shah, Nigam H.
%+ Stanford Center for BioMedical Informatics Research - BMIR , Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier - LIRMM , ORPAILLEUR - INRIA Lorraine - LORIA
%Z INFO/SMILE
%X The volume of publicly available data in biomedicine is constantly increasing. However, these data are stored in different formats and on different platforms. Integrating these data will enable us to facilitate the pace of medical discoveries by providing scientists with a unified view of this diverse information. Under the auspices of the National Center for Biomedical Ontology (NCBO), we have developed the Resource Index--a growing, large-scale ontology-based index of more than twenty heterogeneous biomedical resources. The resources come from a variety of repositories maintained by organizations from around the world. We use a set of over 200 publicly available ontologies contributed by researchers in various domains to annotate the elements in these resources. We use the semantics that the ontologies encode, such as different properties of classes, the class hierarchies, and the mappings between ontologies, in order to improve the search experience for the Resource Index user. Our user interface enables scientists to search the multiple resources quickly and efficiently using domain terms, without even being aware that there is semantics "under the hood."
%2 INFO:INFO_DB;INFO:INFO_WB;INFO:INFO_TT;INFO:INFO_BI;SDV:BIBS
%G English
%2 http://dx.doi.org/10.1016/j.websem.2011.06.005
%2 2010-09
%R 10.1016/j.websem.2011.06.005
%J Journal of Journal of Web Semantics
%2 international
%8 2011-09-00
%V 9
%N 3
%P 316-324
%I Elsevier
%K Semantic Web, ontology-based indexing, semantic annotation, data integration, information mining, information retrieval, biomedical data, biomedical ontologies
%Z NIH Projet NCBO

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