Proposal Preparation

Purpose: Some federal and many foundations within their RFP require submission of an LOI as a prerequisite for advancing to a full (invited) proposal. While this generally short document is not externally evaluated or used to determine funding, it serves various purposes by the funders. An LOI typically contains much of this information in an abbreviated form: tentative project title; summary; budget request; rationale for pursuing; objectives; study design; and expected outcomes/significance.

Processing: An LOI may be processed via RAPSS, a Funding Proposal (FP) created, and  could be routed for approval to the school, chair, and Research and Sponsored Programs (RSP).

Purpose: Some sponsors solicit pre-proposals, and they typically include a project summary and a few supporting documents (i.e., bio sketches, letter of institutional support). At the NSF, for example, the solicitation determines the type of decision to be made upon review. An “invite/no invite” determines who can submit a full proposal.

Processing: The submission process is typically the same as for a full proposal, requiring a RAPSS FP, SC&I chair, and dean approval, and an authorized signature from RSP.

Purpose: Whether a federal agency or foundation submission, it contains all the required information by the sponsor, which may include detailed project plans, staff capabilities, budgets, and facilities, among others. The NSF prioritizes the intellectual merit and broader impacts of a proposed project, but these are goals all investigators should explore in their submissions regardless of the type of submission or funder. All documents, particularly the narrative, should be prepared with the care and thoroughness of a paper being submitted for academic publication.

Processing: Requires a RAPSS FP, SC&I chair, and dean approval, and an authorized signature from RSP.

(Varies by funder; the SC&I grants RPC can assist with these and other documents.)

• Sponsor’s budget and/or RU’s budget template
• Budget justification
• Bio sketches
• Narrative (“science”/”technical”)
• Abstract/summary
• References cited
• Current & pending support (CPS)
• Facilities, equipment, and other resources
• Collaborators & other affiliations (COA)
• Data management plan
• Letter of institutional support
• Letters of Collaboration (LOC)
• Mentoring plan
• Subaward forms

The subaward documents pertain to the work of the subrecipient, not the entirety of the project, and many require the signature of the requesting investigator and an authorized official from the subawardee’s  organization (i.e., its RSP office). If a subagreement is anticipated, the primary institution collects relevant documents from subaward institution(s) for submission to the sponsor during the proposal stage. These may include the following:

• Subrecipient Commitment Form:  Collects disclosure information such as compliance and institutional contact information when Rutgers is the awarding institution. Other institutions typically require similar forms when Rutgers is the subaward institution. Rutgers’ institutional information  can be useful in completing documents sent by an outside institution.  
• Subrecipient Letter of Intent:  Indicates a potential research collaboration as well as confirmation that the subaward institution is prepared to agree should an award be made. Other institutions typically require a subrecipient letter of intent when Rutgers is the subaward institution.  
• Scope of Work: An outline of the expected work to be completed. 
• Budget and Budget Justification:  Categorizes and justifies the expected costs of conducting research.  

• Rutgers’ Electronic Conflict of Interest Disclosures (eCOI+) research certifications are specific project-related disclosures only required by project personnel when an award is received.
• All project personnel named in the proposal must  have  a  current general  financial conflict of interest disclosure.
•  The RPC is designated as the SC&I eCOI+ monitor and must be listed as the departmental reviewer/supervisor for all research-initiated disclosures.

The Non-Human Research Self-Certification tool provides support for Rutgers Investigators when determining if a project is Human Research requiring IRB review. This tool asks a series of questions about the proposed project activities and, based on the responses, issues a self-certification or directs you to contact the IRB for assistance. The proposal’s compliance review by Rutgers’ IRB needs approval before an awarded new  project is set up for a project account by RSP/Grants and Contract Accounting.  Therefore, it is recommended that the PI submit the protocol for IRB approval quickly after the submission of the proposal to the sponsor.   

• If the human subjects’ protocol is not approved, this could delay project set-up which, in turn, might delay the hiring and paying of personnel, along with the purchasing of equipment, etc., for the new project.
• Some sponsors will not issue an award (e.g., NSF) before it receives proof of IRB approval. In some instances, a delay in showing IRB approval may lead to the award not being made.
• The Rutgers’ IRB turnaround time is two to three weeks. If you do not hear back from the IRB by then, please contact the IRB @IRB Office.
• The approval timeline depends on the specifics of the study and the completed documents submitted to the IRB for review. 
• Acquaint yourself with the IRB submission and approval processes by visiting its sites: IRB website, Toolkits, DRAFT Services, Guidance Topics

Creating an Impeccable DMP

A bulletproof data management plan (DMP) is crucial for social science research due to its significant benefits:

1. Ensures good scientific practice throughout the research process.
2. Enhances data security and integrity at all stages of research.
3. Facilitates data sharing after the original research is completed.
4. Improves time efficiency, reproducibility, and safety of research.
5. Helps comply with funder mandates and requirements.
6. Promotes structured thinking about data security, ownership, and file formats before project initiation.
7. Supports responsible research data stewardship.
8. Strengthens grant applications by addressing key data management concerns.
9. Enhances collaboration and data sharing within the scientific community.
10. Potentially increases citation rates for researchers who share their data.

Data Governance: Roles

• Rutgers University’s Governance: Responsible for understanding how data is used and who has the decision-making power.
• Principal Investigator: Defines the roles and responsibilities of team members in data management. In addition, identifies any resources needed such as software, hardware, and training.
• SC&I IT Team: Responsible for data care along with the data creators—faculty, internal, and external users. 

DMP Tool

• For ease of use and to ensure all the required elements of a data plan are accurately included, it is advisable that Principal Investigators and their teams use this “wizard” to construct their data management plans. Rutgers University is an institutional member of the site, and users simply log in with their NetID and password to start creating a customized DMP. 
• Prompts relating to the intended research help customize the plan to best fit the funder’s DMP guidelines.
• The tool houses current templates for DMPs based on the specific requirements in the funder’s guidance documents. These reference documents appear while filling out the templates so cross-referencing through the Internet is not necessary. In addition, sample plans are provided by funder or other trusted parties. [If more authoritative guidance is needed, PIs should consult their Program Officers.]
• Major federal agency calls from the NSF, NIH, and others are included in the DMP tool site, along with prominent foundations’ Requests for Proposals.

Ethical and Legal Compliance

• Access and Restriction / Privacy Policy: Rutgers collects vast amounts of personally identifiable information. This data must be handled according to data access and privacy regulations (e.g., FERPA, GDPR, HIPPA, and institutional).
• Ethical Considerations: Discuss any ethical issues related to data collection, storage, and sharing, including informed consent from participants and the IRB.
• Data Security: Practices govern how the systems that house institutional data are secured as well as backup and disaster recovery protocols.

Data Storage, Backup & Security

• Solutions: Outline where and how data will be stored during the project (e.g., cloud storage, institutional servers). Include backup procedures to prevent data loss, including frequency and methods of backup, and describe plans for long-term data preservation, including the choice of repository and data formats to be used.
• Security Measures: Explain the security measures to protect sensitive or confidential data (e.g., encryption, access controls).
  • Only university-approved cloud-based file storage may be used for Restricted and Controlled data. SharePoint and Box are approved, along with university-supported cloud-based file storage options.
  • Controlled Unclassified Information, which includes Export-Controlled data, is not permitted to be stored in any cloud-storage solution. Restricted and Controlled data is permitted to be stored on university-managed SharePoint accounts. Restricted data is not permitted to sync to nonuniversity-owned devices. Sharing of Restricted data via SharePoint is on a need-to-know basis within the university.
• Data Retention: State the duration for which data will be retained and the rationale behind it.

How To: Methods and Sources

• Data Collection Methods: Explain the methods and instruments used to collect data (e.g., surveys, experiments, simulations).
• Data Sources: Identify the sources from which data will be obtained.
• Data Documentation: Describe how data will be documented throughout the research process. This includes metadata standards, file-naming conventions, version control, and tools used.

Sharing Plans, Restrictions & Licensing

• Data Sharing Plans: State how and when data will be shared with others (e.g., through repositories, upon publication, etc.).
• Access Restrictions: Identify access restrictions and reasoning (e.g., privacy concerns, proprietary data).
• Licensing and Copyright: Specify the licensing terms under which data will be shared (e.g., Creative Commons licenses).

Resources

• Rutgers’ Office of Advance Research Computing 
• Rutgers Libraries’ Data Management Planning 
• NSF: Preparing Your Data Management and Sharing Plan 
• NIH: Data Management and Sharing Policy