NIH expects that researchers will take steps to maximize scientific data sharing, but acknowledges that certain factors (i.e., ethical, legal, or technical) may necessitate limiting sharing, to some extent. Foreseeable limitations (e.g. bounds of consent documentation, substantial risk to the privacy of data subjects, restrictions imposed by regulations or contracts), the proposed method for disseminating such data, and the rationale must be described in the DMSPs for the NIH to assess.
Potential examples of justifiable factors include:
- informed consent will not permit or will limit the scope or extent of sharing and future research use
- existing consent (e.g., for previously collected biospecimens) prohibits sharing or limits the scope or extent of sharing and future research use
- privacy or safety of research participants would be compromised or place them at greater risk of re-identification or suffering harm, and protective measures such as de-identification and Certificates of Confidentiality would be insufficient
- explicit federal, state, local, or Tribal law, regulation, or policy prohibits disclosure
- restrictions imposed by existing or anticipated agreements (e.g., with third party funders, with partners, with repositories, with Health Insurance Portability and Accountability Act (HIPAA) covered entities that provide Protected Health Information under a data use agreement, through licensing limitations attached to materials needed to conduct the research)
- datasets cannot practically be digitized with reasonable efforts
Examples of reasons that would generally not be justifiable factors limiting scientific data sharing include:
- data are considered to be too small
- data that researchers anticipate will not be widely used
- data are not thought to have a suitable repository
NIH respects and recognizes Tribal sovereignty and American Indian and Alaska Native (AI/AN) communities’ data sharing concerns, and NIH has proposed additional considerations when working with Tribes in the draft supplemental information on “Responsible Management and Sharing of AI/AN Participant Data.”