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Finding useful data across multiple biomedical data repositories using DataMed

Publication Abstract

Ohno-Machado, Lucila, George C. Alter, Susanna-Assunta Sansone, Ian Fore, Jeffrey Grethe, Hua Xu, Alejandra Gonzalez-Beltran, Philippe Rocca-Serra, Anupama E. Gururaj, Elizabeth Bell, Ergin Soysal, Nansu Zong, and Hyeon-eui Kim. 2017. "Finding useful data across multiple biomedical data repositories using DataMed." Nature Genetics, 49(6): 816-819.

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.

DOI:10.1038/ng.3864 (Full Text)

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