Research Guides

Data Management

This guide outlines the how's and why's of managing research data at the CUNY Grad Center.

FAIR

Data Management Plans should be based on FAIR Principles:

  • Findable - using descriptive keywords and DOIs.
  • Accessible - easy to retrieve data residing in a repository. 
  • Interoperable - Using open formats and consistent vocabulary.
  • Reusable - Clear reuse licenses and strong documentation.

See more.

Data management plans

Many key granting organizations, like NSF, NIH, NEH and more, now require submitters to include a Data Management Plan as part of their application. These plans outline what steps the applicant will take to collect, safeguard, archive, and make available the data used for the research in question.  A plan should not be an onerous step, but rather documentation of steps you have taken or plan to take in respect to file formats and organization, metadata and documentation, storage and security, and sharing and access. 

The particular requirements of a data management plan will vary among funding agencies, so it is best to always consult the agency. However, there are a few attributes that are common to all data management plans, including:

  • A description of the type(s) of data to be produced
  • Methods of how the data will be collected and who will be responsible for data management
  • Standards you will use to describe your data (metadata standards)
  • Backup and storage procedures
  • Provisions for long-term archiving and preservation
  • Access policies and provisions for secondary uses: will it be available to others? 
  • Any protection or security measures taken to protect participant confidentiality

Funding agency guidelines

Federal agencies

Many federal funding agencies require a DMP with every funding request. Each agency or directorate creates its own set of policies for data management. SPARC (the Scholarly Publishing and Academic Resources Coalition) has compiled an excellent resource with information but the data management and data sharing requirements from all the federal funding agencies.

NNLM Toolkit for the NIH Data Management and Sharing Policy

SPARC's Data Sharing Requirements by Federal Agency

National Science Foundation (NSF)

FAQ's about Data Management and Sharing

Data Management Plan Requirements by Directorate

Data Archiving Policy

Grant Proposal Guide

 

Private agencies

Private foundations may have requirements or guidelines related to data collection and data sharing, which may or may not include a DMP. Requirements may vary by program. Check directly with each organization for specifics.

Gates Foundation: Open access policy mandates that publications will be open access, and that "data underlying published research results will be accessible and open immediately."

Alfred P. Sloan Foundation: "How will your data and code be shared, annotated, cited, and archived? What else will you do to make your findings reproducible by other researchers?" for general projects, and for those generating "information products," there is another section that is a fuller DMP. 

Ford Foundation: Requires a Creative Commons license for all grant-funded work.

Gordon and Betty Moore Foundation: "As part of the foundation grant development process, potential grantees are required to develop a Data Management and Sharing Plan with their foundation grant team. All data used in or developed in whole or in part by foundation-funded projects (and that can be shared in a manner consistent with applicable laws) will be made widely available and freely shared as soon as possible. If data used in foundation-funded projects are owned by an additional party other than the grantee, we do not require it to be released, but the grantee will use its best efforts to encourage the data owners to make it openly and freely available."

MacArthur Foundation: The foundation "expects openness in research and freedom of access to research results and, when feasible, to the underlying data by persons with a serious interest in the research... grant-funded impact studies should generally be registered in a field-appropriate registry..." (from their broader intellectual property policy).

Examples of data management plans

DMPTool

DMPTool Blog | Guidance & resources for your data management plan

The DMPTool is an online tool that includes data management plan templates for many of the large funding agencies that require such plans. The tool includes general guidance, links to helpful documentation, issues to consider, and specific questions to think about as you prepare your data management plan. Space is provided to compose a response for each of the main areas that your funding agency would like for you to address in your plan. You can save and come back to your plan as often as you like. When you are finished, you can export your plan in plain text format and insert it into your grant proposal.  It is a good way to start and or complete your data management plan.

CITI Training

All CUNY faculty members, postdoctoral scholars, graduate and undergraduate students involved in human subjects research as key personnel must complete the applicable Basic Course (e.g. HSR for Social & Behavioral Faculty, Graduate Students, & Postdoctoral Fellows) in the protection of human subjects prior to Institutional Review Board (IRB) approval of their protocol.  More info here.

Rebecca Banchik is the GC's Director of the Human Research Protection Program.

 Adrienne Klein, is the GC's Director of Special Projects and Research Integrity Officer, of Research and Sponsored Programs.