Required Application Instructions

It is critical that applicants follow the instructions in the SF424 (R&R) Application Guide, except where instructed to do otherwise (in this FOA or in a Notice from the NIH Guide for Grants and Contracts). Conformance to all requirements (both in the Application Guide and the FOA) is required and strictly enforced. Applicants must read and follow all application instructions in the Application Guide as well as any program-specific instructions noted in Section IV. When the program-specific instructions deviate from those in the Application Guide, follow the program-specific instructions. Applications that do not comply with these instructions may be delayed or not accepted for review.

Part 1. Overview Information
Part 2. Full Text of the Announcement
Section I. Funding Opportunity Description
Section II. Award Information
Section III. Eligibility Information
Section IV. Application and Submission Information
Section V. Application Review Information
Section VI. Award Administration Information
Section VII. Agency Contacts
Section VIII. Other Information

The overall goal of the NIH Ruth L. Kirschstein National Research Service Award (NRSA) program is to help ensure that a diverse pool of highly trained scientists is available in appropriate scientific disciplines to address the Nation's biomedical, behavioral, and clinical research needs. In order to accomplish this goal, NRSA training programs are designed to train individuals to conduct research and to prepare for research careers. More information about NRSA programs may be found at the Ruth L. Kirschstein National Research Service Award (NRSA) website.

Purpose and Background Information

The NRSA program has been the primary means of supporting predoctoral and postdoctoral research training programs since enactment of the NRSA legislation in 1974. Research training activities can be in basic biomedical or clinical sciences, in behavioral or social sciences, in health services research, or in any other discipline relevant to the NIH mission.

Institutional NRSA programs allow the Training Program Director/Principal Investigator (Training PD/PI) to select the trainees and develop a program of coursework, research experiences, and technical and/or professional skills development appropriate for the selected trainees. Each program should provide high-quality research training and offer opportunities in addition to conducting mentored research. The grant offsets the cost of stipends, tuition and fees, and training related expenses, including health insurance, for the appointed trainees in accordance with the approved NIH support levels.

The purpose of this FOA is to solicit applications for graduate training programs in Big Data Science, for the expressed purpose of training the next generation of scientists who will develop computational and quantitative approaches and tools needed by the biomedical research community to work with Big Data in the biomedical sciences. This proposed type of training should prepare qualified individuals for careers in developing new technologies and methods that will allow biomedical researchers to maximize the value of the growing volume and complexity of biomedical "big data." The career outcomes of individuals supported by NRSA training programs include both research-intensive careers in academia and industry and research-related careers in various sectors.

Training for the BD2K Initiative

Extracting useful knowledge from biomedical Big Data is a major limiting factor to understanding health and disease. The focus of the Big Data to Knowledge (BD2K) Initiative is to support the research and development of innovative and transformative approaches and tools with the goal of maximizing and accelerating the utility of Big Data and data science in biomedical research. For the purpose of this FOA, biomedical is broadly defined to include biomedical, behavioral, and social science research focused on health.

To address the growing need for skilled researchers to fully utilize the vast amount of heterogeneous biomedical Big Data there must be an increase in the number of individuals: (1) trained in developing tools, methods, and analyses to make Big Data useful, and (2) knowledgeable about how to use the tools, methods, and analyses. Thus, the primary goals of training and education efforts for the BD2K Initiative are 1) to increase the number of expert biomedical data scientists, and 2) to elevate general data science competencies of all biomedical scientists.

Data Science training and education needs in the biomedical workforce vary greatly based on an individual’s prior knowledge and their intended use of data. Thus, BD2K programs to support training, education, and career development reflect a variety of needs within the workforce.

• For biomedical scientists to become conversant in data science and learn to utilize existing tools, courses and open educational resources are available.
• To address the growing need for specialists in biomedical data science, predoctoral students and early career scientists are supported.
• To foster the development of new interdisciplinary teams consisting of biomedical scientists and data scientists, BD2K is collaborating with the National Science Foundation.
• To train a diverse workforce, under-resourced institutions serving diverse populations are developing data science curriculum and providing short-term research experiences for students and faculty.

To ensure that BD2K’s training and education efforts have maximum impact in generating knowledge, educational resources should be findable, accessible, interoperable, and reusable (FAIR). The FAIR principles are applied in the development of an Educational Resource Discovery Index that will help biomedical scientists find and access the most appropriate data science educational resources to meet their training and educational needs. The BD2K Training Coordination Center (TCC) is developing this Educational Resource Discovery Index and is providing coordination and communication among those interested in Big Data training and education (the BD2K Training Consortium).

Taken together, the BD2K training and educational programs will improve the ability of the entire biomedical science community to utilize the growing volume and complexity of data. Additional information about BD2K s portfolio of training and education awards is available online.

Predoctoral Training Programs in Biomedical Big Data Science

This FOA focuses on long-term training of predoctoral students by soliciting applications for new graduate training programs in Big Data Science. These training grants will help ensure that a diverse and highly trained workforce is available to assume leadership roles related to developing computational and quantitative approaches, technologies, methods, and tools needed by the biomedical research community to work with biomedical Big Data.

This predoctoral training initiative is different from most currently funded NIH training programs in that it will:

• Require that trainees work effectively at the intersection of these three scientific areas computer science/informatics, statistics/mathematics, and biomedical science;
• Require extensive coursework in both advanced statistical and computational techniques;
• Expect active participation of training faculty from all of these three scientific disciplines who will work collaboratively across disciplines as co-mentors of trainees in Big Data Science; and
• Develop the skills required to participate in a team approach to solving data-intensive biomedical problems, while also nurturing the skills necessary to be an independent investigator in Big Data Science.

The purpose of the BD2K training program is to produce graduates who will have the required multidisciplinary skill sets for careers in which they will have the potential to develop new quantitative approaches, methods, and tools needed by the biomedical research community to harness the opportunities Big Data provides.

Training Program Features: The foundational training program should include courses in all three scientific areas (computer science/informatics, statistics/mathematics, and biomedical science, broadly defined), reflecting the student's background and need. The program should incorporate the following elements, with a focus on Big Data: 1) rotations in academe and industry, 2) team approaches to interdisciplinary research, 3) an emphasis on principles and practices that promote rigorous experimental design and transparency to enhance reproducibility (NOT-OD-16-034), and 4) joint mentorship. Because Big Data Science is interdisciplinary in nature, it is expected that trainees will acquire during the training experience competency in all three relevant areas computer science/informatics, statistics/mathematics, and biomedical science and expertise in aspects of data science that are essential to biomedical science. The training should include those aspects of computer science/informatics and statistics/mathematics that are directly relevant to the biomedical sciences. Since this program is not focused on any particular disease or sets of diseases, the knowledge and skills learned should be generally applicable to all biomedical big data research problems.

Courses should include knowledge that is deep in data science and broad in the application domain of biomedical science. Each of the trainees should acquire a common, core set of knowledge in data science, which typically includes informatics/computer science (e.g. Databases, ontologies, algorithms, optimization, visualization, etc.), advanced statistics (e.g. Advanced modeling techniques, networks, multiplicities, etc.), and machine learning.

Programs are expected to identify trainees from a variety of undergraduate backgrounds such as the biomedical sciences, computer science, engineering, informatics, mathematics, physics, and statistics. All trainees are expected to acquire a core set of knowledge in data science, but their primary application areas may differ. It is anticipated that by the end of their training, trainees will have acquired the necessary experience to pursue research in biomedical Big Data Science.

Big Data Science Training Programs will prepare students to be independent researchers and at the same time prepare them to work in teams since solving the challenges presented by Big Data will often involve a team science approach to problem solving. Therefore, training programs are encouraged to provide trainees with the experience of working as part of a team of individuals with expertise and skill sets in disparate domains in order to solve important biomedical Big Data problems.

In addition, training programs should ensure that trainees have multiple mentors, from disciplines necessary for capitalizing on biomedical Big Data.

Successful graduates of these programs will be prepared for research-oriented roles in academic institutions, not-for-profit research institutes, governmental and public health agencies, pharmaceutical and biomedical software companies, and health care organizations. This initiative is not intended to prepare trainees for careers emphasizing planning, deployment, maintenance, or administration of computer systems in health care, public health, medical education or research. The emphasis in this program is on the development of new knowledge that advances biomedical Data Science as a scientific discipline.

Training activities focus on the data science which can be applied to biomedical, behavioral, and social sciences research focused on health relevant to the NIH mission. The Training Program Director/Principal Investigator(s) (Training PD/PI(s)), together with participating training faculty, is responsible for developing the program's approaches -- selecting trainees and developing a curriculum of study and research experiences necessary to provide a high quality research training experience. Multiple PD/PI applications are strongly encouraged in order to include expertise in all three areas essential to biomedical Big Data Science. In most cases, the multiple PDs/PIs will have demonstrated evidence of strong prior collaboration.

The proposed Training Program in Big Data Science may complement other ongoing research training and career development programs at the applicant institution, but it must have a Big Data focus that distinguishes it from any other training programs at the applicant institution.
Applications for training programs that focus exclusively on one or two of the BD2K relevant scientific areas or on just a few diseases will not be considered responsive.

Primary Organizational Focus of the Training Program: NIH strongly encourages institutions with expertise in the three areas discussed above who have not previously received training grants from NIH to apply. NIH also encourages institutions that currently have multiple NIH training grants and who wish now to apply for a BD2K training grant to consider drawing on and taking advantage of existing training activities, through collaborative approaches to expand beyond what their current training programs offer to create a new unique, effective Big Data training program.

Within the framework of the NRSA program’s longstanding commitment to excellence and projected need for investigators in particular areas of research, attention must be given to recruiting trainees from racial or ethnic groups underrepresented in the biomedical, behavioral, and clinical sciences, individuals with disabilities, and individuals from disadvantaged backgrounds.

The Training PD/PI, together with participating training faculty, should limit appointments to individuals who are committed to a career in biomedical Big Data Science and who plan to remain on the training grant or in a non-NRSA research experience until completion of the doctoral degree. The Training PD/PI, together with participating training faculty, should also encourage and provide training in the skills necessary for trainees to apply for subsequent peer-reviewed support.

See Section VIII. Other Information for award authorities and regulations.

NIH grants policies as described in the NIH Grants Policy Statement will apply to the applications submitted and awards made in response to this FOA.

Higher Education Institutions

• Public/State Controlled Institutions of Higher Education
• Private Institutions of Higher Education

The following types of Higher Education Institutions are always encouraged to apply for NIH support as Public or Private Institutions of Higher Education:

• Hispanic-serving Institutions
• Historically Black Colleges and Universities (HBCUs)
• Tribally Controlled Colleges and Universities (TCCUs)
• Alaska Native and Native Hawaiian Serving Institutions
• Asian American Native American Pacific Islander Serving Institutions (AANAPISIs)

Governments

• Indian/Native American Tribal Governments (Federally Recognized)
• Indian/Native American Tribal Governments (Other than Federally Recognized)
• U.S. Territory or Possession

Other

• Native American Tribal Organizations (other than Federally recognized tribal governments)

The sponsoring institution must assure support for the proposed program. Appropriate institutional commitment to the program includes the provision of adequate staff, facilities, and educational resources that can contribute to the planned program.

The applicant institution(s) must have a strong and high quality research program in biomedical Big Data Science that includes diverse and complex data types, such as genomic, other -omic, imaging, phenotypic, exposure, etc. The applicant institution(s) must have the requisite faculty and facilities to conduct the proposed institutional program. In many cases, it is anticipated that the proposed program will complement, but be distinct from, other ongoing research training programs occurring at the applicant institution. It is expected that a substantial number of program faculty will have active biomedical peer-reviewed Big Data Science research projects involving a variety of data types in the biomedical sciences in which participating trainees may gain relevant experiences consistent with their research interests and goals.

Non-domestic (non-U.S.) Entities (Foreign Institutions) are not eligible to apply.
Non-domestic (non-U.S.) components of U.S. Organizations are not eligible to apply.
Foreign components, as defined in the NIH Grants Policy Statement, are not allowed.

Applicant Organizations

Applicant organizations must complete and maintain the following registrations as described in the SF 424 (R&R) Application Guide to be eligible to apply for or receive an award. All registrations must be completed prior to the application being submitted. Registration can take 6 weeks or more, so applicants should begin the registration process as soon as possible. The NIH Policy on Late Submission of Grant Applications states that failure to complete registrations in advance of a due date is not a valid reason for a late submission.

• Dun and Bradstreet Universal Numbering System (DUNS) - All registrations require that applicants be issued a DUNS number. After obtaining a DUNS number, applicants can begin both SAM and eRA Commons registrations. The same DUNS number must be used for all registrations, as well as on the grant application.
• System for Award Management (SAM) (formerly CCR) Applicants must complete and maintain an active registration, which requires renewal at least annually. The renewal process may require as much time as the initial registration. SAM registration includes the assignment of a Commercial and Government Entity (CAGE) Code for domestic organizations which have not already been assigned a CAGE Code.
• NATO Commercial and Government Entity (NCAGE) Code Foreign organizations must obtain an NCAGE code (in lieu of a CAGE code) in order to register in SAM.
• eRA Commons - Applicants must have an active DUNS number and SAM registration in order to complete the eRA Commons registration. Organizations can register with the eRA Commons as they are working through their SAM or Grants.gov registration. eRA Commons requires organizations to identify at least one Signing Official (SO) and at least one Program Director/Principal Investigator (PD/PI) account in order to submit an application.
• Grants.gov Applicants must have an active DUNS number and SAM registration in order to complete the Grants.gov registration.

Program Directors/Principal Investigators (PD(s)/PI(s))

All PD(s)/PI(s) must have an eRA Commons account. PD(s)/PI(s) should work with their organizational officials to either create a new account or to affiliate their existing account with the applicant organization in eRA Commons.If the PD/PI is also the organizational Signing Official, they must have two distinct eRA Commons accounts, one for each role. Obtaining an eRA Commons account can take up to 2 weeks.

Any individual(s) with the skills, knowledge, and resources necessary to carry out the proposed research training program as the Training Program Director/Principal Investigator (Training PD/PI) is invited to work with his/her organization to develop an application for support. Individuals from underrepresented racial and ethnic groups as well as individuals with disabilities are always encouraged to apply for NIH support.

For institutions/organizations proposing multiple PDs/PIs, visit the Multiple Program Director/Principal Investigator Policy and submission details in the Senior/Key Person Profile (Expanded) Component of the SF 424 (R&R) Application Guide.

Multiple PDs/PIs are encouraged. The PDs/PIs should be established investigators in the scientific areas relevant to biomedical Big Data Science and capable of providing both administrative and scientific leadership to the development and implementation of the proposed training program. The PDs/PIs will be expected to monitor and assess the program and submit all documents and reports as required. Since the focus of the training is in the area of developing new approaches and tools for manipulating, analyzing, and interpreting Big Data, the PD/PIs for this type of training program should collectively encompass expertise from all three major scientific areas, including demonstrated research leadership in computer science/informatics, statistics/mathematics, and biomedical science. The biomedical Big Data research program at the institution must not focus on one disease or sets of related diseases.

The contact PD/PI must ensure that the appropriate faculty work collaboratively and in a sustained manner across scientific disciplines and organizational lines to jointly mentor trainees.

This FOA does not require cost sharing as defined in the NIH Grants Policy Statement.

Only one application per institution, identified by a unique DUNS number, will be accepted.

The NIH will not accept duplicate or highly overlapping applications under review at the same time. This means that the NIH will not accept:

• A new (A0) application that is submitted before issuance of the summary statement from the review of an overlapping new (A0) or resubmission (A1) application.
• A resubmission (A1) application that is submitted before issuance of the summary statement from the review of the previous new (A0) application.
• An application that has substantial overlap with another application pending appeal of initial peer review (see NOT-OD-11-101).

Program faculty should have strong records as researchers, including recent publications and successful competition for research support in the area of the proposed research training program. Program faculty should also have a record of research training, including successful, former trainees who have established productive careers relevant to the NIH mission. Researchers from diverse backgrounds, including racial and ethnic minorities, persons with disabilities, and women are encouraged to participate as mentors.

Biomedical Big Data Science is interdisciplinary and includes three major scientific areas: (1) computer science or informatics; (2) statistics and mathematics; and (3) biomedical sciences. It anticipated that the training program will have a sufficient number of mentors in all three areas, including biomedical sciences researchers, and will utilize the idea of multiple mentorship. Participating training faculty should include investigators who develop new technologies and practical tools, who generate and utilize Big Data, and who have a variety of biomedical expertise, from clinical to basic sciences, and with multiple disease specialties.

The individual to be trained must be a citizen or a noncitizen national of the United States or have been lawfully admitted for permanent residence at the time of appointment. Additional details on citizenship, training period, and aggregate duration of support are available in the NIH Grants Policy Statement.

Predoctoral trainees must have received significant didactic training in at least one of the three major scientific areas in Big Data Science (computer science or informatics, statistics and mathematics, biomedical sciences) or a related area by the beginning date of their NRSA appointment and must be enrolled in a research doctoral program in an area relevant to Big Data Science. Health-professional students who wish to interrupt their studies for a year or more to engage in full-time research training before completing their formal training programs are also eligible.

Because Big Data Science includes the three major scientific areas described above, the program should strive to have a mix of trainees with backgrounds in these three scientific areas. While a mix is important for preparing students for Team Science research in the future, students also must develop the skills to be independent researchers in biomedical Big Data Science.

All trainees are required to pursue their research training full time, normally defined as 40 hours per week, or as specified by the sponsoring institution in accordance with its own policies. Appointments are normally made in 12-month increments, and no trainee may be appointed for less than 9 months during the initial period of appointment, except with prior approval of the NIH awarding unit.

Applicants must obtain the SF424 (R&R) application package associated with this funding opportunity using the Apply for Grant Electronically button in this FOA or following the directions provided at Grants.gov.

It is critical that applicants follow the instructions in the SF424 (R&R) Application Guide including Supplemental Grant Application Instructions except where instructed in this funding opportunity announcement to do otherwise. Conformance to the requirements in the Application Guide is required and strictly enforced. Applications that are out of compliance with these instructions may be delayed or not accepted for review.

For information on Application Submission and Receipt, visit Frequently Asked Questions Application Guide, Electronic Submission of Grant Applications.

All page limitations described in the SF424 (R&R) Application Guide and the Table of Page Limits must be followed.

Instructions for Application Submission

The following section supplements the instructions found in the SF424 (R&R) Application Guide and should be used for preparing an application to this FOA.

Follow all instructions provided in the SF424 (R&R) Application Guide.

Follow all instructions provided in the SF424 (R&R) Application.

Follow all instructions provided in the SF424 (R&R) Application, with the following additional modifications:

Project Summary/Abstract. Provide an abstract of the entire application. Include the objectives, rationale and design of the research training program, as well as key activities in the training plan. Indicate the planned duration of appointments, the projected number of trainees including their levels (i.e., predoctoralland intended trainee outcomes.

Other Attachments. A plan must be provided for the appointment of an Advisory Committee to monitor progress. Composition, responsibilities, frequency of meetings, and other relevant information should be included. Do not name specific individuals who will be appointed to the Advisory Committee, but describe the composition of the Advisory Committee in terms of the role and the desired expertise of members. A plan for Advisory Committee approval and selection of participants should be included. Describe how the Advisory Committee will function in providing oversight of the development, implementation, and evaluation of recruitment strategies, the recruitment and retention of candidates, and the evaluation of the overall effectiveness of the program. Please name your file Advisory_Committee.pdf .

The filename provided for each Other Attachment will be the name used for the bookmark in the electronic application in eRA Commons.

Follow all instructions provided in the SF424 (R&R) Application

Follow all instructions provided in the SF424 (R&R) Application.

Follow all instructions provided in the SF424 (R&R) Application Guide

Follow all instructions provided in the SF424 (R&R) Application Guide with the following additional modifications:

• Include all personnel other than the Training PD(s)/PI(s) in the Other Personnel section, including clerical and administrative staff.

The PHS 398 Research Training Program Plan Form is comprised of the following sections:

Training Program

Faculty, Trainees, and Training Record

Other Training Program Sections

Appendix

Follow all instructions provided in the SF424 (R&R) Application Guide with the following additional modifications:

Particular attention must be given to the required Training Data Tables.

Program Plan

Proposed Training.

The training program should be designed to ensure that by the end of the training period, trainees would have received sufficient breadth in knowledge and skills in the areas that complement their undergraduate degree, if applicable,, as well as depth in complementary BD2K areas. Because trainees will enter the program with different knowledge and skill sets, a trainee's program may have to be customized.

Some of the common elements of a successful training program should include the following:

Courses: Courses should expose trainees to the basic concepts and working knowledge in the three scientific areas of Big Data Science. It is incumbent on the applicant to define a set of core concepts that graduating students will master, even if their research projects are highly specialized.

Team Science Approach to Problem Solving: Trainees working together as a team or as part of an interdisciplinary research group effort to solve a Big Data Science challenge provide an opportunity for individuals from disparate domains of knowledge and skill sets to come together to solve important problems. Problem-based learning through a team approach should be seriously considered in the design of a core curriculum. Special attention should be paid to the rigorous experimental design and transparency to enhance reproducibility of results. Visit this URL for additional information: http://grants.nih.gov/reproducibility/index.htm.

Rotations and External Internships: Rotations are widely recognized as effective means to introduce students to the broadest range of the myriad types of data sets that are a challenge to Big Data Science. Rotations in basic, computer, and clinical laboratories are encouraged after trainees have had sufficient course work to provide basic training in all three relevant areas of Big Data Science. Experiences in academic, industrial, and other relevant settings are also encouraged as a way to introduce students to a variety of creative approaches to conducting Big Data research.

Joint Mentorship: One way to enhance training and communication among disciplines is for trainees to have mentors from more than one of the three major scientific areas. Arrangements for joint mentorship of trainees should be considered as one of the goals of this training program. Peer-to-peer mentoring should also be encouraged between more senior trainees and more junior trainees.

Reproducibility of Research Results: An emphasis on the practices that promote the reproducibility of results, such as scientific and rigorous design and implementation of experiments, usage of analysis methods based on scientifically sound statistical principles, and the sharing of code, data, protocols, and other information necessary for reproducing research.

Forums for Intellectual Exchanges: It is important for trainees to have opportunities to interact with other trainees and faculty from other Big Data training programs to discuss published articles and research in progress and to interact with visiting scholars. Mechanisms for fostering intellectual exchanges may include journal clubs; seminars by students, faculty, and outside speakers; and annual retreats.

Individual Development Plans (IDP): Each student is encouraged to have an IDP in place at the beginning of their appointment to the program. The IDP should be developed jointly by the trainee and her/his mentors and should be reviewed at a minimum annually (http://grants.nih.gov/grants/guide/notice-files/NOT-OD-13-093.html).

Transition from the Training Program to Dissertation Research: It is expected that at some point during the training, appointees should have the opportunity to continue their dissertation research under sponsors whose research is primarily involved with biomedical Big Data Science. Trainees should be encouraged to complete their dissertation research in the area of biomedical Big Data Science.

If funds for curriculum development are requested, the applicant should describe the new courses, how they will differ from and build upon existing ones, and how they utilize appropriate technology. The applicant should describe how course materials will be disseminated and shared widely and how they can be used, modified, and updated by others.

Institutional Environment and Commitment to the Program.

The sponsoring institution must assure support for the proposed program including assurance that sufficient time will be allowed for the PDs/PIs and other Program Faculty to contribute to the proposed program. The application must include a signed letter, on institutional letterhead, that describes the applicant institution’s commitment to the planned program. Appropriate institutional commitment to the program includes the provision of adequate staff, facilities, and educational resources that can contribute to the planned program. This commitment may also include features such as PD/PI salary, stipend or tuition support for individuals involved in the proposed training program, or other commitments essential to a successful training program. Institutions with ongoing research training, student development, or career development programs that receive external funding should explain what distinguishes the proposed program from existing ones at the same trainee level, how the programs will synergize, if applicable, whether trainees are expected to transition from one support program to another, and how the training faculty, pool of potential trainees, and resources are sufficiently robust to support the proposed program in addition to existing ones.

Recruitment and Retention Plan to Enhance Diversity

Individuals are required to comply with the instructions for Recruitment and Retention Plan to Enhance Diversity as provided in Chapter 8 of the SF424 (R&R) Application Guide.

Plan for Instruction in the Responsible Conduct of Research

Individuals are required to comply with the instructions for Plan for Instruction in the Responsible Conduct of Research as provided in the SF424 (R&R) Application Guide.

Appendix

Do not use the Appendix to circumvent page limits. Follow all instructions for the Appendix as described in the SF424 (R&R) Application Guide.

All instructions in the SF424 (R&R) Application Guide must be followed.

See Part 1. Section III.1 for information regarding the requirement for obtaining a unique entity identifier and for completing and maintaining active registrations in System for Award Management (SAM), NATO Commercial and Government Entity (NCAGE) Code (if applicable), eRA Commons, and Grants.gov

Part I. Overview Information contains information about Key Dates and times. Applicants are encouraged to submit applications before the due date to ensure they have time to make any application corrections that might be necessary for successful submission. When a submission date falls on a weekend or Federal holiday, the application deadline is automatically extended to the next business day.

Organizations must submit applications to Grants.gov (the online portal to find and apply for grants across all Federal agencies). Applicants must then complete the submission process by tracking the status of the application in the eRA Commons, NIH’s electronic system for grants administration. NIH and Grants.gov systems check the application against many of the application instructions upon submission. Errors must be corrected and a changed/corrected application must be submitted to Grants.gov on or before the application due date and time. If a Changed/Corrected application is submitted after the deadline, the application will be considered late. Applications that miss the due date and time are subjected to the NIH Policy on Late Application Submission.

Applicants are responsible for viewing their application before the due date in the eRA Commons to ensure accurate and successful submission.

Information on the submission process and a definition of on-time submission are provided in the SF424 (R&R) Application Guide.

This initiative is not subject to intergovernmental review.

All NIH awards are subject to the terms and conditions, cost principles, and other considerations described in the NIH Grants Policy Statement. The National Research Service Award (NRSA) policies apply to this program. An NRSA appointment may not be held concurrently with another Federally sponsored fellowship, traineeship, or similar Federal award that provides a stipend or otherwise duplicates provisions of the NRSA.

Pre-award costs are allowable only as described in the NIH Grants Policy Statement. Note, however, that pre-award costs are not allowable charges for stipends or tuition/fees on institutional training grants because these costs may not be charged to the grant until a trainee has actually been appointed and the appropriate paperwork submitted to the NIH awarding component..

Applications must be submitted electronically following the instructions described in the SF424 (R&R) Application Guide. Paper applications will not be accepted.

Applicants must complete all required registrations before the application due date. Section III. Eligibility Information contains information about registration.

For assistance with your electronic application or for more information on the electronic submission process, visit Applying Electronically. If you encounter a system issue beyond your control that threatens your ability to complete the submission process on-time, you must follow the Guidelines for Applicants Experiencing System Issues. For assistance with application submission, contact the Application Submission Contacts in Section VII.

Important reminders:

All PD(s)/PI(s) must include their eRA Commons ID in the Credential field of the Senior/Key Person Profile Component of the SF424(R&R) Application Package. Failure to register in the Commons and to include a valid PD/PI Commons ID in the credential field will prevent the successful submission of an electronic application to NIH.

The applicant organization must ensure that the DUNS number it provides on the application is the same number used in the organization’s profile in the eRA Commons and for the System for Award Management (SAM). Additional information may be found in the SF424 (R&R) Application Guide.

See more tips for avoiding common errors.

Upon receipt, applications will be evaluated for completeness by the Center for Scientific Review and for responsiveness by the BD2K Subcommittee on Training. Applications that are incomplete and/or nonresponsive will not be reviewed.

Applicants are required to follow the instructions for post-submission materials, as described in NOT-OD-13-030.

Only the review criteria described below will be considered in the review process. As part of the NIH mission, all applications submitted to the NIH in support of biomedical and behavioral research are evaluated for scientific and technical merit through the NIH peer review system.

Reviewers will provide an overall impact score to reflect their assessment of the likelihood that the proposed training program will prepare individuals for successful, productive scientific research careers and thereby exert a sustained influence on the research field(s) involved, in consideration of the following review criteria and additional review criteria (as applicable for the project proposed).

Reviewers will consider each of the review criteria below in the determination of the merit of the training program, and give a separate score for each. When applicable, the reviewers will consider relevant questions in the context of proposed short-term training. An application does not need to be strong in all categories to be judged likely to have major scientific impact.

Training Program and Environment

• Are the research facilities and research environment conducive to preparing trainees for successful careers as biomedical Big Data research scientists?
• Are the objectives, design and direction of the proposed research training program likely to ensure effective training?
• Do the courses, where relevant, and research experiences provide opportunities for trainees to acquire state-of-the-art scientific knowledge, methods, and tools that are relevant to the goals of the biomedical Big Data training program?
• Does the program provide appropriate inter- or multidisciplinary research training opportunities?
• Is the proposed training program likely to ensure trainees will be well prepared for research-intensive and research-related Big Data Science careers?
• Is the level of institutional commitment to the training program, including administrative and research training support, sufficient to ensure the success of the program?
• Is it clear how the proposed training program is distinguished from other externally funded training programs at the institution?

In addition, for this FOA

• Does the program or training track prepare trainees to develop novel methodologies and techniques applicable to Big Data?
• Are innovative approaches used to build on existing programs? Does the research environment include large amounts of data of varying types and complexities?
• Curriculum (when applicable): Is the new curriculum novel and innovative? Are the plans to make these curricula widely and openly available adequate? Where applicable, are the training materials in a form that can be modified, updated, and tailored by others? Does the program utilize appropriate technology to enhance, facilitate, and personalize the learning process?

Training Program Director(s)/Principal Investigator(s) (PD(s)/PI(s))

• Does the PD/PI have the scientific background, expertise in biomedical Big Data, and administrative and training experience to provide strong leadership, direction, management, and administration of the proposed research training program?
• Does the PD/PI plan to commit sufficient effort to ensure the program s success?

For applications designating multiple PDs/PIs:

• Is a strong justification provided that the multiple PD/PI leadership approach will benefit the training program and the trainees?
• Is a strong and compelling leadership approach evident, including the designated roles and responsibilities, governance, and organizational structure consistent with and justified by the aims of the training program and the complementary expertise of the PDs/PIs?

In addition, for this FOA

• Do the Training PDs/PIs have the background, expertise, and experience in Big Data Science research?
• Is sufficient administrative and research training support provided for the program or training track?
• Is leadership sufficiently strong to develop and maintain close collaborations across departments?

Preceptors/Mentors

• Are sufficient numbers of experienced preceptors/mentors with appropriate expertise and funding available to support the number and level of trainees (including short-term trainees, if applicable) proposed in the application?
• Do the preceptors/mentors have strong records as researchers, including recent publications and successful competition for research support in areas directly related to the proposed research training program?
• Do the preceptors/mentors have strong records of training individuals at the level of trainees (including short-term trainees, if applicable) proposed in the program?
• Are appropriate plans in place to ensure that preceptors lacking sufficient research training experience are likely to provide strong and successful mentoring?

In addition, for this FOA

• Is there evidence of collaboration amongst the preceptors/mentors in biomedical Big Data Science projects? Are all the preceptors/mentors involved in Big Data research?
• Do the preceptors'/mentors' expertise collectively cover all of the areas that are critical to biomedical Big Data science?

Trainees

• Is a recruitment plan proposed with strategies likely to attract well-qualified trainees for the training program?
• Is there a competitive applicant pool of sufficient size and quality, at each of the proposed levels (predoctoral), to ensure a successful training program?
• Are there well-defined and justified selection and re-appointment criteria as well as retention strategies?
• Do the trainees have the requisite undergraduate degrees relevant to biomedical Big Data to be successful in this training program?

Training Record

• How successful are the trainees (or, for new applications, other past students/postdoctorates in similar training) in completing the program?
• Has the training program ensured that trainees are productive (or, for new applications, other past students/postdoctorates in similar training) in terms of research accomplishments, publication of research conducted during the training period, and subsequent training appointments and fellowship or career development awards?
• How successful are the trainees (or, for new applications, other past students/postdoctorates in similar training) in achieving productive scientific careers as evidenced by successful competition for research science positions in industry, academia, government or other research venues; grants; receipt of honors, awards, or patents; high-impact publications; promotion to scientific leadership positions; and/or other such measures of success?
• Does the program propose a rigorous evaluation plan to assess the quality and effectiveness of the training? Are effective mechanisms in place for obtaining feedback from current and former trainees?

In addition, for this FOA

• If the training program/training track is new, how successful have previous trainees of the PDs/PIs been in the ways mentioned above?

As applicable for the project proposed, reviewers will evaluate the following additional items while determining scientific and technical merit, and in providing an overall impact score, but will not give separate scores for these items.

Protections for Human Subjects

Generally not applicable. Reviewers should bring any concerns to the attention of the Scientific Review Officer.

Inclusion of Women, Minorities, and Children

Generally not applicable. Reviewers should bring any concerns to the attention of the Scientific Review Officer.

Vertebrate Animals

Generally not applicable. Reviewers should bring any concerns to the attention of the Scientific Review Officer.

Biohazards

Generally not applicable. Reviewers should bring any concerns to the attention of the Scientific Review Officer.

Resubmissions

For Resubmissions, the committee will evaluate the application as now presented, taking into consideration the responses to comments from the previous scientific review group and changes made to the project.

Renewals

Not Applicable

Revisions

Not Applicable

As applicable for the project proposed, reviewers will consider each of the following items, but will not give scores for these items, and should not consider them in providing an overall impact score.

Recruitment Plan to Enhance Diversity

Peer reviewers will separately evaluate the recruitment plan to enhance diversity after the overall score has been determined. Reviewers will examine the strategies to be used in the recruitment of individuals from underrepresented groups. The plan will be rated as ACCEPTABLE or UNACCEPTABLE, and the consensus of the review committee will be included in an administrative note in the summary statement.

Training in the Responsible Conduct of Research

All applications for support under this FOA must include a plan to fulfill NIH requirements for instruction in the Responsible Conduct of Research (RCR). Taking into account the specific characteristics of the training program, the level of trainee experience, and the particular circumstances of the trainees, the reviewers will evaluate the adequacy of the proposed RCR training in relation to the following five required components: 1) Format - Does the plan satisfactorily address the format of instruction, e.g. lectures, coursework and/or real-time discussion groups, including face-to-face interaction? (A plan involving only on-line instruction is not acceptable.); 2) Subject Matter Does the plan include a sufficiently broad selection of subject matter, such as conflict of interest, authorship, data management, human subjects and animal use, laboratory safety, research misconduct, research ethics? 3) Faculty Participation - Does the plan adequately describe how faculty will participate in the instruction? For renewal applications, are all training faculty who served as course directors, speakers, lecturers, and/or discussion leaders during the past project period named in the application? 4) Duration of Instruction - Does the plan meet the minimum requirements for RCR, i.e., at least eight contact hours of instruction? 5) Frequency of Instruction Does the plan meet the minimum requirements for RCR, i.e., at least once during each career stage (undergraduate, post-baccalaureate, predoctoral, postdoctoral, and faculty levels) and at a frequency of no less than once every four years?

Plans and past record will be rated as ACCEPTABLE or UNACCEPTABLE, and the summary statement will provide the consensus of the review committee.

Select Agent Research

Reviewers will assess the information provided in this section of the application, including (1) the Select Agent(s) to be used in the proposed research, (2) the registration status of all entities where Select Agent(s) will be used, (3) the procedures that will be used to monitor possession use and transfer of Select Agent(s), and (4) plans for appropriate biosafety, biocontainment, and security of the Select Agent(s).

Budget and Period of Support

Reviewers will consider whether the budget and the requested period of support are fully justified and reasonable in relation to the proposed research. If support for curriculum development is requested, reviewers will consider whether the budget is appropriately justified.

Applications will be evaluated for scientific and technical merit by (an) appropriate Scientific Review Group(s), convened by the Center for Scientific Review in accordance with NIH peer review policy and procedures, using the stated review criteria. Assignment to a Scientific Review Group will be shown in the eRA Commons.

As part of the scientific peer review, all applications:

• May undergo a selection process in which only those applications deemed to have the highest scientific and technical merit (generally the top half of applications under review) will be discussed and assigned an overall impact score.
• Will receive a written critique.

Appeals of initial peer review will not be accepted for applications submitted response to this FOA.

Applications will be assigned to National Library of Medicine. Applications will compete for available funds with all other recommended applications submitted in response to BD2K training program FOAs. Following initial peer review, recommended applications will receive a second level of review by the National Library of Medicine Board of Regents. The following will be considered in making funding decisions:

• Scientific and technical merit of the proposed project as determined by scientific peer review.
• Availability of funds.
• Relevance of the proposed project to program priorities.
• Geographic considerations.

After the peer review of the application is completed, the PD/PI will be able to access his or her Summary Statement (written critique) via the eRA Commons. Refer to Part 1 for dates for peer review, advisory council review, and earliest start date

Information regarding the disposition of applications is available in the NIH Grants Policy Statement.

If the application is under consideration for funding, NIH will request "just-in-time" information from the applicant as described in the NIH Grants Policy Statement.

A formal notification in the form of a Notice of Award (NoA) will be provided to the applicant organization for successful applications. The NoA signed by the grants management officer is the authorizing document and will be sent via email to the grantee’s business official.

Awardees must comply with any funding restrictions described in Section IV.5. Funding Restrictions. Selection of an application for award is not an authorization to begin performance. Any costs incurred before receipt of the NoA are at the recipient's risk. These costs may be reimbursed only to the extent considered allowable pre-award costs.

Any application awarded in response to this FOA will be subject to terms and conditions found on the Award Conditions and Information for NIH Grants website. This includes any recent legislation and policy applicable to awards that is highlighted on this website.

All NIH grant and cooperative agreement awards include the NIH Grants Policy Statement as part of the NoA. For these terms of award, see the NIH Grants Policy Statement Part II: Terms and Conditions of NIH Grant Awards, Subpart A: General and Part II: Terms and Conditions of NIH Grant Awards, Subpart B: Terms and Conditions for Specific Types of Grants, Grantees, and Activities. More information is provided at Award Conditions and Information for NIH Grants.

Recipients of federal financial assistance (FFA) from HHS must administer their programs in compliance with federal civil rights law. This means that recipients of HHS funds must ensure equal access to their programs without regard to a person’s race, color, national origin, disability, age and, in some circumstances, sex and religion. This includes ensuring your programs are accessible to persons with limited English proficiency. HHS recognizes that research projects are often limited in scope for many reasons that are nondiscriminatory, such as the principal investigator’s scientific interest, funding limitations, recruitment requirements, and other considerations. Thus, criteria in research protocols that target or exclude certain populations are warranted where nondiscriminatory justifications establish that such criteria are appropriate with respect to the health or safety of the subjects, the scientific study design, or the purpose of the research.

For additional guidance regarding how the provisions apply to NIH grant programs, please contact the Scientific/Research Contact that is identified in Section VII under Agency Contacts of this FOA. HHS provides general guidance to recipients of FFA on meeting their legal obligation to take reasonable steps to provide meaningful access to their programs by persons with limited English proficiency. Please see http://www.hhs.gov/ocr/civilrights/resources/laws/revisedlep.html. The HHS Office for Civil Rights also provides guidance on complying with civil rights laws enforced by HHS. Please see http://www.hhs.gov/ocr/civilrights/understanding/section1557/index.html; and http://www.hhs.gov/ocr/civilrights/understanding/index.html. Recipients of FFA also have specific legal obligations for serving qualified individuals with disabilities. Please see http://www.hhs.gov/ocr/civilrights/understanding/disability/index.html. Please contact the HHS Office for Civil Rights for more information about obligations and prohibitions under federal civil rights laws at http://www.hhs.gov/ocr/office/about/rgn-hqaddresses.html or call 1-800-368-1019 or TDD 1-800-537-7697. Also note it is an HHS Departmental goal to ensure access to quality, culturally competent care, including long-term services and supports, for vulnerable populations. For further guidance on providing culturally and linguistically appropriate services, recipients should review the National Standards for Culturally and Linguistically Appropriate Services in Health and Health Care at http://minorityhealth.hhs.gov/omh/browse.aspx?lvl=2&lvlid=53.

Institutional NRSA training grants must be administered in accordance with the current NRSA section of the NIH Grants Policy Statement - Institutional Research Training Grants.

Leave Policies

The taxability of stipends is described in the NIH Grants Policy Statement. Policies regarding the Ruth L. Kirschstein-NRSA payback obligation are explained in the NIH Grants Policy Statement.

As specified in the NIH Revitalization Act of 1993, Kirschstein-NRSA recipients incur a service payback obligation for the first 12 months of postdoctoral support. Policies regarding the Ruth L. Kirschstein-NRSA payback obligation are explained in the NIH Grants Policy Statement; and more details are in the Frequently Asked Questions. Officials at the grantee institution have the responsibility of explaining the terms of the payback requirements to all prospective trainees before appointment to the training grant. Additionally, all trainees recruited into the training program should be provided with information related to the career options that might be available when they complete the program. The suitability of such career options as methods to satisfy the NRSA service payback obligation should be discussed.

Awards made primarily for educational purposes are exempted from the PHS invention requirements and thus invention reporting is not required, as described in the NIH Grants Policy Statement.

Not Applicable

When multiple years are involved, awardees will be required to submit the Research Performance Progress Report (RPPR) annually. Continuation support will not be provided until the required forms are submitted and accepted.

Failure by the grantee institution to submit required forms in a timely, complete, and accurate manner may result in an expenditure disallowance or a delay in any continuation funding for the award.

The Federal Funding Accountability and Transparency Act of 2006 (Transparency Act), includes a requirement for awardees of Federal grants to report information about first-tier subawards and executive compensation under Federal assistance awards issued in FY2011 or later. All awardees of applicable NIH grants and cooperative agreements are required to report to the Federal Subaward Reporting System (FSRS) available at www.fsrs.gov on all subawards over $25,000. See the NIH Grants Policy Statement for additional information on this reporting requirement.

• The institution must submit a completed Statement of Appointment (PHS Form 2271) for each trainee appointed or reappointed to the training grant for 8 weeks or more. Grantees must submit the PHS 2271 data electronically using the xTrain system. More information on xTrain is available at xTrain (eRA Commons). An appointment or reappointment may begin any time during the budget period, but not before the budget period start date of the grant year.
• A notarized statement verifying possession of permanent residency documentation must be submitted with the Statement of Appointment (PHS Form 2271). Individuals with a Conditional Permanent Resident status must first meet full (non-conditional) Permanent Residency requirements before receiving support.
• Termination Notice: Within 30 days of the end of the total support period, the institution must submit a Termination Notice (PHS Form 416-7) via xTrain for each trainee appointed for eight weeks or more. Trainees with service payback requirements must notify the NIH of any change in address and submit Annual Payback Activities Certification Forms (PHS Form 6031-1) until the payback service obligation is satisfied.

In carrying out its stewardship of human resource-related programs, the NIH may request information essential to an assessment of the effectiveness of this program from databases and from participants themselves. Participants may be contacted after the completion of this award for periodic updates on various aspects of their employment history, publications, support from research grants or contracts, honors and awards, professional activities, and other information helpful in evaluating the impact of the program.

We encourage inquiries concerning this funding opportunity and welcome the opportunity to answer questions from potential applicants.

eRA Commons Help Desk (Questions regarding eRA Commons registration, submitting and tracking an application, documenting system problems that threaten submission by the due date, post submission issues)
Finding Help Online: http://grants.nih.gov/support/ (preferred method of contact)
Telephone: 301-402-7469 or 866-504-9552 (Toll Free)

Grants.gov Customer Support (Questions regarding Grants.gov registration and submission, downloading forms and application packages)
Contact Center Telephone: 800-518-4726
Web ticketing system: https://grants-portal.psc.gov/ContactUs.aspx
Email: [email protected]

GrantsInfo (Questions regarding application instructions and process, finding NIH grant resources)
Email: [email protected] (preferred method of contact)
Telephone: 301-710-0267

Jane Ye, PhD
National Library of Medicine (NLM)
Telephone: 301-594-4882
Email: [email protected]

Mark Caprara, PhD
Center for Scientific Review (CSR)
Telephone: 301-613-5228
Email: [email protected]

Dwight Mowery
National Library of Medicine (NLM)
Telephone: 301-496-4221
Email: [email protected]

Recently issued trans-NIH policy notices may affect your application submission. A full list of policy notices published by NIH is provided in the NIH Guide for Grants and Contracts. All awards are subject to the terms and conditions, cost principles, and other considerations described in the NIH Grants Policy Statement.

Awards are made under the authorization of Section 487 of the Public Health Service Act as amended (42 USC 288) and under Federal Regulations 42 CFR 66.