Finding useful data across multiple biomedical data repositories using DataMed View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-06

AUTHORS

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

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. More... »

PAGES

816

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/ng.3864

DOI

http://dx.doi.org/10.1038/ng.3864

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1085600484

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28546571


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