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

17 Pages Posted: 9 Jul 2018 Publication Status: Accepted

See all articles by Clement Jonquet

Clement Jonquet

Stanford University - Center for Biomedical Informatics Research; University of Montpellier - Laboratory of Informatics, Robotics and Microelectronics (LIRMM)

Paea LePendu

Stanford University - Center for Biomedical Informatics Research

Sean Falconer

Stanford University - Center for Biomedical Informatics Research

Adrien Coulet

Stanford University - Center for Biomedical Informatics Research; University of Lorraine - Lorraine Research Laboratory in Computer Science and Its Applications (LORIA)

Natasha F. Noy

Stanford University - Center for Biomedical Informatics Research

Mark A. Musen

Stanford University - Center for Biomedical Informatics Research

Nigam H. Shah

Stanford University - Center for Biomedical Informatics Research

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: ontology-based indexing, semantic annotation, data integration, information mining

Suggested Citation

Jonquet, Clement and LePendu, Paea and Falconer, Sean and Coulet, Adrien and Noy, Natasha F. and Musen, Mark A. and Shah, Nigam H., NCBO Resource Index: Ontology-Based Search and Mining of Biomedical Resources (2011). Journal of Web Semantics First Look 9_3_7, Available at SSRN: https://ssrn.com/abstract=3199526 or http://dx.doi.org/10.2139/ssrn.3199526

Clement Jonquet (Contact Author)

Stanford University - Center for Biomedical Informatics Research ( email )

1265 Welch Road
Stanford, CA
United States

University of Montpellier - Laboratory of Informatics, Robotics and Microelectronics (LIRMM) ( email )

163 rue Auguste Broussonnet
Montpellier
France

Paea LePendu

Stanford University - Center for Biomedical Informatics Research ( email )

1265 Welch Road
Stanford, CA
United States

Sean Falconer

Stanford University - Center for Biomedical Informatics Research ( email )

1265 Welch Road
Stanford, CA
United States

Adrien Coulet

Stanford University - Center for Biomedical Informatics Research ( email )

1265 Welch Road
Stanford, CA
United States

University of Lorraine - Lorraine Research Laboratory in Computer Science and Its Applications (LORIA)

615, rue du Jardin Botanique
Villers-lès-Nancy, 54506
France

Natasha F. Noy

Stanford University - Center for Biomedical Informatics Research ( email )

1265 Welch Road
Stanford, CA
United States

Mark A. Musen

Stanford University - Center for Biomedical Informatics Research ( email )

1265 Welch Road
Stanford, CA
United States

Nigam H. Shah

Stanford University - Center for Biomedical Informatics Research ( email )

1265 Welch Road
Stanford, CA
United States

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