Read your Funding Opportunity Announcement (FOA) and look at your NIH Institute Center or Offices (ICO) data management and sharing policies. Certain FOA's and ICO's outline specific expectations for data management and sharing on top of the baseline NIH Policy. For example, does your ICO outline a specific repository that all of the data funded through them must be deposited into?
Determine your timeline especially in conjunction with possible external collaborators. If you plan to apply for NIH funding this year, give high priority to developing your DMSP.
Identify if you can share all or parts of your data. This depends factors like any existing Data Use Agreements, the level of re-identification risk to your population, and any explicit federal, state, local, or Tribal law, regulation, or policy, amongst other things. Unacceptable reasons to limit data sharing include a lack of suitable repository, desire to keep data private to publish on later, data being considered too small, or where the researcher believes there is no anticipated wide use.
Locate an appropriate repository to deposit your research data and documentation.
Assess your project and data management practices. Consider practices you currently have or need to develop. Research Data & Digital Scholarship and your subject librarians are happy to talk through your workflows and practices.
A Checklist produced for use at the EUDAT summer school to discuss how FAIR the participant's research data were and what measures could be taken to improve FAIRness.
Created by the Australian Research Data Commons, the FAIR data self assessment tool will help assess the ‘FAIRness’ of a dataset and determine how to enhance its FAIRness
