Reflecting on the wide-ranging accomplishments of the NIH Big Data to Knowledge (BD2K) initiative shows how much progress has been made and reveals new areas for exploration. It is time to set directions and priorities for the next generation of biomedical data science research and development. As a first step, the National Library of Medicine has issued a Request for Information (RFI) on behalf of NIH entitled “Next Generation Data Science Challenges in Health and Biomedicine.” The RFI was announced in the NIH Guide to Grants and Contracts on September 29, 2017. We welcome your thoughts by November 1, 2017.
During the past five years, NIH has substantially invested in a data science infrastructure, developing tools, resources, and workforce components for a digital research ecosystem for health and biomedicine. Building on this foundation, the landscape of data science research has evolved, and continues to evolve, both within and beyond NIH. To help NIH strengthen and expand the scope of its investments in data science, NLM seeks information from public and private organizations (e.g., universities and industry) and from individuals on promising data science research directions in health and biomedicine.
Responses to this RFI must be submitted by November 1, 2017. Responses should be provided in narrative form, up to three pages per topic, with embedded links to pertinent supplemental information if needed. NLM and NIH hope you will share the RFI link widely among all stakeholder groups, including researchers, clinicians, administrators, and others, whether in industry, private, or public sectors, in all areas of biomedical, social/behavioral, and health-related research. Your responses will help shape the direction of data science research at NLM and NIH.
The RFI identifies three focal areas that span the research and training interests of all Institutes and Centers at NIH. The three areas are:
- New data science research in the context of health and biomedicine. Input might address such topics as Data Driven Discovery and Data Driven Health Improvement.
- New initiatives relating to open science and research reproducibility. Input might address such topics as Advanced Data Management and Intelligent and Learning Systems for Health.
- Workforce development and new partnerships. Input might address such topics as Workforce Development and Diversity and New Stakeholder Partnerships
Respondents may also suggest important data science topics of their own.
Whether in a single topic area or all of them, NLM invites researchers, clinicians, organizations, industry representatives, and other interested parties to provide input on:
- Research areas that could benefit most from advanced data science methods and approaches;
- Data science methods that need updating, or gap areas where new approaches are needed;
- Priorities for new data science research; and
- Appropriate partnerships and settings for expanded data science research.
As a reminder, responses to this RFI must be submitted by November 1, 2017. Responses should be provided in narrative form, up to three pages per topic, with embedded links to pertinent supplemental information if needed.
Please direct all inquiries to:
Valerie Florance, PhD
National Library of Medicine (NLM)