On behalf of the National Institutes of Health (NIH), the National Library of Medicine (NLM) seeks community input through a Request...
Environmental Health & Toxicology Update from the National Library of Medicine
Feedback Needed: RFI on Next-Generation Data Science Challenges in Health and Biomedicine
On behalf of the National Institutes of Health (NIH), the National Library of Medicine (NLM) seeks community input through aRequest for Information (RFI)on new data science research initiatives that could address key challenges currently faced by researchers, clinicians, administrators, and others, in all areas of biomedical, social/behavioral, and health-related research. The field of data science is broad in scope, encompassing approaches for the generation, characterization, management, storage, analysis, visualization, integration, and use of large, heterogeneous data sets that have relevance to health and biomedicine.
Data science undergirds the broad and interdependent objectives of theNIH Strategic Plan. Information about data science research directions that could lead to breakthroughs in any or all NIH interest areas is welcomed, whether applicable across wide swaths of health and biomedicine, or focused on particular research domains.
NLM requests information on the three focal areas listed below:
Promising directions for new data science research in the context of health and biomedicine. Input might addresstopics such as Data Driven Discovery and Data Driven Health Improvement.
Promising directions for new initiatives relating to open science and research reproducibility. Input might addresstopics such as Advanced Data Management and Intelligent and Learning Systems for Health.
Promising directions for workforce development and new partnerships. Input might addresstopics such as Workforce Development and Diversity and New Stakeholder Partnerships.
Response to this RFI must be submitted to theNIH NLM websiteby November 1, 2017. Responses should be provided in a narrative form of up to three pages per topic, with links to pertinent supplemental information if needed. No attachments will be accepted. No proprietary, classified, confidential, or sensitive information should be included inthis response. Please direct all inquiries to Valerie Florance, PhD, NLM, 301.496.4621,NLMEPInfo@mail.nih.gov.
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