What is the Vivli Clinical Data Repository?

Vivli is an online platform for researchers to share anonymized, individual participant-level data from clinical trials and other clinical studies. Researchers can use Vivli to share clinical data to meet the NIH Data Management and Sharing policy and to share data underlying their scientific articles (now required by many journals).

Vivli accepts all clinical data that is anonymized, prospectively planned, and protocol driven. That includes clinical trials, registries, and observational studies.

UCSF is an institutional member of Vivli, meaning that our researchers are able to upload and share data for free by creating an account with their UCSF email. Qualified investigators are then able to apply to Vivli for access to the shared data for re-use in future studies.

Useful Vivli resources

Tips and tricks for using our membership with Vivli

  • Plan ahead! The data deposit process can take from 1-2 weeks.
  • Use your UCSF email to create your Vivli account - this is how they will associate you with our membership.
  • We have a signed master Data Contributor Agreement with Vivli, but PIs will need to review the agreement and sign a form saying they acknowledge it as part of the submission process.
  • UCSF membership covers deposits up to 500GB, if you go over that amount there is a $10k fee.
  • Special notes for depositing data:
    • Funding source: Enter N/A@vivli.org for the mandatory invoicing email field
    • Data Contributor Agreement - institutional official - leave blank (covered by master agreement)
    • Once you sign that you acknowledge the data contributor agreement your info will be processed by Vivli - this takes about a week. Once that is finalized you will be notified that you can upload your data.


Contact Ariel Deardorff at ariel.deardorff@ucsf.edu with questions about using Vivli.

More data sharing resources

Sharing clinical research data takes time and advanced preparation to ensure that patient consent and other controls are in place, and that data has been properly prepared and de-identified. Learn more about planning for data management and sharing with these resources:

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