利用 DataMed 在多个生物医学数据存储库中查找有用数据。
Finding useful data across multiple biomedical data repositories using DataMed.
机构信息
Health System Department of Biomedical Informatics, University of California, San Diego, La Jolla, California, USA.
Veterans Administration San Diego Healthcare System, San Diego, California, USA.
出版信息
Nat Genet. 2017 May 26;49(6):816-819. doi: 10.1038/ng.3864.
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.
拓宽在多个存储库中搜索数据的范围的价值已被生物医学研究界所认可。作为美国国立卫生研究院（NIH）大数据到知识倡议的一部分，我们与国际研究人员、服务提供商和知识专家合作，开发和测试数据索引和搜索引擎，这些索引和搜索引擎基于从各种存储库中的不同数据集提取的元数据。DataMed 的设计目的是为数据提供类似于 PubMed 为科学文献提供的服务。DataMed 支持数据集的可发现性和可访问性。这些特性——以及互操作性和可重用性——构成了 FAIR 原则的四个方面，以促进当今大数据密集型科学领域的知识发现。
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