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Finding useful data across multiple biomedical data repositories using DataMed

delete2017-05-26
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OA
AI
L
Lucila Ohno‐Machado *
S
Susanna‐Assunta Sansone
G
George Alter
I
Ian Fore
J
Jeffrey S. Grethe
H
Hua Xu
A
Alejandra González-Beltrán
P
Philippe Rocca‐Serra
A
Anupama E. Gururaj
E
Elizabeth Bell
E
Ergin Soysal
N
Nansu Zong
H
Hyeoneui Kim
DOI:10.1038/ng.3864delete
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Abstract

Abstract

En 中文
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 reusabilitycompose the four FAIR principles to facilitate knowledge discovery in today's big data-intensive science landscape.
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Journal

Nature Reviews Endocrinology cover
Nature Reviews Endocrinology
IF:
40
Papers:
1.0W
Citations:
10.5W

Organization

N
national institutes of health (nih) - usa
Scholars:
10.3W
Papers: 8.2W
Citations: 111
University of California System cover
University of California System
Scholars:
37.5W
Papers: 33.7W
Citations: 6.6K
U
university of oxford
Scholars:
9.7W
Papers: 8.6W
Citations: 137
U
University of Michigan
Scholars:
6.4W
Papers: 5.3W
Citations: 124
U
university of michigan system
Scholars:
9.1W
Papers: 8.6W
Citations: 133
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