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
N1 - Funding Information:
This project is funded by grant U24AI117966 from NIAID, NIH, as part of the BD2K program.
Publisher Copyright:
© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
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.
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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 -