Finding useful data across multiple biomedical data repositories using DataMed

Lucila Ohno-Machado; Susanna Assunta Sansone; George Alter; Ian Fore; Jeffrey Grethe; Hua Xu; Alejandra Gonzalez-Beltran; Philippe Rocca-Serra; Anupama E. Gururaj; Elizabeth Bell; Ergin Soysal; Nansu Zong; Hyeon Eui Kim

doi:10.1038/ng.3864

Finding useful data across multiple biomedical data repositories using DataMed

Lucila Ohno-Machado, Susanna Assunta Sansone, George Alter, Ian Fore, Jeffrey Grethe, Hua Xu, Alejandra Gonzalez-Beltran, Philippe Rocca-Serra, Anupama E. Gururaj, Elizabeth Bell, Ergin Soysal, Nansu Zong, Hyeon Eui Kim

Artificial Intelligence and Informatics

Research output: Contribution to journal › Review article › peer-review

Abstract

The value of broadening searches for data across multiple repositories has been identified by the biomedical research community. As part of the US National Institutes of Health (NIH) Big Data to Knowledge initiative, we work with an international community of researchers, service providers and knowledge experts to develop and test a data index and search engine, which are based on metadata extracted from various data sets in a range of repositories. DataMed is designed to be, for data, what PubMed has been for the scientific literature. DataMed supports the findability and accessibility of data sets. These characteristics-along with interoperability and reusability-compose the four FAIR principles to facilitate knowledge discovery in today's big data-intensive science landscape.

Original language	English (US)
Pages (from-to)	816-819
Number of pages	4
Journal	Nature Genetics
Volume	49
Issue number	6
DOIs	https://doi.org/10.1038/ng.3864
State	Published - Jun 1 2017

ASJC Scopus subject areas

Genetics

Access to Document

10.1038/ng.3864

Cite this

@article{adad7f81a94346a98e430050d730ea3a,

title = "Finding useful data across multiple biomedical data repositories using DataMed",

abstract = "The value of broadening searches for data across multiple repositories has been identified by the biomedical research community. As part of the US National Institutes of Health (NIH) Big Data to Knowledge initiative, we work with an international community of researchers, service providers and knowledge experts to develop and test a data index and search engine, which are based on metadata extracted from various data sets in a range of repositories. DataMed is designed to be, for data, what PubMed has been for the scientific literature. DataMed supports the findability and accessibility of data sets. These characteristics-along with interoperability and reusability-compose the four FAIR principles to facilitate knowledge discovery in today's big data-intensive science landscape.",

author = "Lucila Ohno-Machado and Sansone, {Susanna Assunta} and George Alter and Ian Fore and Jeffrey Grethe and Hua Xu and Alejandra Gonzalez-Beltran and Philippe Rocca-Serra and Gururaj, {Anupama E.} and Elizabeth Bell and Ergin Soysal and Nansu Zong and Kim, {Hyeon Eui}",

year = "2017",

month = jun,

day = "1",

doi = "10.1038/ng.3864",

language = "English (US)",

volume = "49",

pages = "816--819",

journal = "Nature Genetics",

issn = "1061-4036",

publisher = "Nature Publishing Group",

number = "6",

}

TY - JOUR

T1 - Finding useful data across multiple biomedical data repositories using DataMed

AU - Ohno-Machado, Lucila

AU - Sansone, Susanna Assunta

AU - Alter, George

AU - Fore, Ian

AU - Grethe, Jeffrey

AU - Xu, Hua

AU - Gonzalez-Beltran, Alejandra

AU - Rocca-Serra, Philippe

AU - Gururaj, Anupama E.

AU - Bell, Elizabeth

AU - Soysal, Ergin

AU - Zong, Nansu

AU - Kim, Hyeon Eui

PY - 2017/6/1

Y1 - 2017/6/1

N2 - The value of broadening searches for data across multiple repositories has been identified by the biomedical research community. As part of the US National Institutes of Health (NIH) Big Data to Knowledge initiative, we work with an international community of researchers, service providers and knowledge experts to develop and test a data index and search engine, which are based on metadata extracted from various data sets in a range of repositories. DataMed is designed to be, for data, what PubMed has been for the scientific literature. DataMed supports the findability and accessibility of data sets. These characteristics-along with interoperability and reusability-compose the four FAIR principles to facilitate knowledge discovery in today's big data-intensive science landscape.

AB - The value of broadening searches for data across multiple repositories has been identified by the biomedical research community. As part of the US National Institutes of Health (NIH) Big Data to Knowledge initiative, we work with an international community of researchers, service providers and knowledge experts to develop and test a data index and search engine, which are based on metadata extracted from various data sets in a range of repositories. DataMed is designed to be, for data, what PubMed has been for the scientific literature. DataMed supports the findability and accessibility of data sets. These characteristics-along with interoperability and reusability-compose the four FAIR principles to facilitate knowledge discovery in today's big data-intensive science landscape.

UR - http://www.scopus.com/inward/record.url?scp=85019721343&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85019721343&partnerID=8YFLogxK

U2 - 10.1038/ng.3864

DO - 10.1038/ng.3864

M3 - Review article

C2 - 28546571

AN - SCOPUS:85019721343

SN - 1061-4036

VL - 49

SP - 816

EP - 819

JO - Nature Genetics

JF - Nature Genetics

IS - 6

ER -

Finding useful data across multiple biomedical data repositories using DataMed

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this