Accurate Linking of Grants and Topics in Science
Accurate Linking of Grants and Topics in Science
批准号:
1548907
负责人:
Kevin Boyack
金额:
$5.55万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-01 至 2016-02-29
中文摘要
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英文摘要
Understanding the outcomes associated with R&D funding requires accurate linking of funding with the papers produced by the funded work. This proposal develops a methodology to accurately link grants with topics, an important challenge for the development of a rigorous, quantitative understanding and analysis of science policy. The research will provide methods to accurately and consistently identify coherent research areas and systematically link those topic areas to research funding and research output, such as scientific publications, using text and other features. The ability to accurately link grants and topics in a consistent way would be an important advance in the usefulness of STAR METRICS data. In addition to developing a methodology, this project also establishes the accuracy of existing NIH grant-to-article linkage data, and develop grant-to-article linkage data for non-NIH grants -- data which are not readily available. More accurate grant-article and grant-topic linkages will facilitate other research and be important to the STAR METRICS platform.
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会议论文
EAGER: Identifying Emergent Opportunities in Science
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批准号:1142795
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项目类别:Standard Grant
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资助金额:$20.0万
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财政年份:2011
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负责人:Kevin Boyack
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依托单位:
海外基金