Request for Information (RFI): Training Needs in Response to Big Data to Knowledge (BD2K) Initiative

Notice Number: NOT-HG-13-003

Key Dates

Release Date: February 20, 2013
Response Date: March 15, 2013

Issued by

National Institutes of Health (NIH)


The National Institutes of Health is launching Big Data to Knowledge (BD2K), an initiative to address how best to manage and utilize the large amounts of biomedical data that new technologies can generate ( This initiative resulted from a set of recommendations from the Data and Informatics Working Group to the Advisory Committee to the Director, NIH (Data and Informatics Working Group). As part of the its response to the recommendations, NIH has established a working group to develop plans to implement new programs to increase training in this area, and this working group intends to convene a workshop to discuss training and education needs in how to manage and utilize large complex data sets.  Prior to the workshop, NIH wishes to collect information and relevant materials that will help inform the discussions of the workshop participants.


The era of Big Data has arrived for biomedical research, bringing with it immense challenges as well as spectacular opportunities. In this context, Big Data is meant to reflect the challenges facing biomedical researchers of all stripes in accessing, organizing, analyzing, and integrating datasets that are increasingly larger, more complex, and more numerous. These data are also of diverse types that must be integrated, including imaging, phenotypic, molecular, exposure, health, and many other types of biomedical, behavioral and clinical data. While used here for convenience, the phrase Big Data is intended to be shorthand for the reality that biomedical research has become a data-intensive enterprise.

Advances in biomedical sciences using Big Data will require more scientists with appropriate expertise and skills, some of whom will be critical members of interdisciplinary teams. NIH is interested in increasing funding for long- and short-term training at all professional levels, in areas essential for accessing, organizing, analyzing, and integrating biomedical Big Data (e.g., computational biology, biostatistics, bioinformatics, the quantitative sciences, and related areas).

Information Requested 

The workshop will address the long- and short-term training needs of professionals and trainees with the purposes of increasing the number of: (1) informaticians and computational and quantitative scientists who wish to apply their skills and knowledge in the biomedical, behavioral and clinical sciences and (2) biomedical, behavioral, and clinical scientists who have the requisite knowledge and skills to effectively access, organize, analyze, and integrate large and complex data sets. To aid in planning this workshop, responses are being sought from the extramural community on the following:

Characteristics and Contents of Plans for Cross-Training Biomedical, Behavioral, Clinical, Computational, and Quantitative Scientists and Informaticians at All Career Levels:

  • Doctoral and postdoctoral training programs that will be needed to expand the capabilities of the targeted groups to use Big Data, with special attention to the training and mentoring environments.
  • Short-term training, including course content that will be needed to cross-train the targeted groups and undergraduates.
  • New curriculum and other training materials that will be needed to cross-train the targeted groups and undergraduates.

Evaluation of Workforce Skills and Knowledge

If you are a researcher, please describe your research area; the knowledge and skill set competencies of individuals you are recruiting or have recruited to handle large complex datasets; how long it took you to fill the position(s); and whether you have encountered difficulties in retaining these qualified individuals.

If you have hired recently trained graduates in the biomedical, behavioral, clinical, informatics, computational, or quantitative sciences, please describe the knowledge and skill sets they possessed or lacked - in handling large and complex datasets.

If you are a recent graduate employed in handling large datasets, please describe your scientific discipline; what courses, skills, and experiences prepared you for this job; and what courses, skills, and experiences you would have liked to have had to prepare you for this job.

Development of a Diverse Research Workforce

With respect to the above points, please provide information about important, additional programmatic enhancements that are needed to develop, foster, and maintain a diverse research workforce cross-trained in the areas specified in this RFI. NIH is particularly interested in efforts to engage individuals from backgrounds underrepresented in biomedical, behavioral, clinical, informatics, computational, or quantitative sciences, including underrepresented racial and ethnic minorities, persons with disabilities, persons from disadvantaged backgrounds and women.

Submitting a Response

To aid in planning the workshop, NIH is seeking responses from the extramural community, including graduate students, postdoctoral fellows, scientists, clinicians, scientific societies, NIH grantee institutions, and industry.

To respond to any of the points above or others deemed relevant to the development of new NIH training and education activities to address the Big Data challenge, please identify the critical issues(s) and provide your comments, recommended approaches or suggestions in bullet form. Please limit your responses to two pages. Responders are free to address any or all of the above items. All comments must be submitted electronically to:

Responses to this RFI will be accepted through Friday, March 15, 2013. Responders will receive an electronic confirmation acknowledging receipt of a response, but will not receive individualized feedback on any submissions. No basis for claims against the U.S. Government shall arise as a result of a response to this request for information or from the Government s use of such information.


Please direct all inquiries to:

Michelle Dunn, Ph.D.
Program Director
National Cancer Institute/NIH