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“It is imperative that the NIH view scientific data as the principle result of scientific research – not the conference presentation or journal publication describing the data." https://www.amia.org/news-and-publications/press-release/amia-nih-misses-mark-data-sharing-proposals …
Data is a scientific multiplier: if a grant funded project develops a good dataset, dozens of papers from groups not funded by the grant will be the result. And yet NLM does not value data creation in its proposals, only methods (I've been told this directly). CC: @NLMdirector
Publicly funded research is a scientific multiplier: If a grant project develops a good approach, hundreds of papers from groups across different fields will be the result.
I'm not knocking methods grants, both methods and data are needed. But in AI research for many clinical/biomedical tasks, the data to enable methods is lacking. Given that AI methods developed outside biomedicine that can be applied here, data is commonly the bottleneck.
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