Consistent with UCSF’s mission of advancing health worldwide is the translation of scientific discoveries into new products and services for use by the community. Increasingly, data is required to build, test, and validate healthcare innovations for community benefit.
The Research Data Archive is a list of datasets previously curated by UCSF researchers which are available to license.
The Research Data Archive is:
- a way for companies to access previously curated datasets efficiently.
- available only to U.S. entities and for use in the U.S.
- only for purposes approved by UCSF, on a case-by-case basis.
- available only on the terms of the license agreement.
- subject to a $22,500* annual subscription fee, per dataset.
- accessible for approved applicants within 30 days from application submission.
The Research Data Archive does not:
- Contain protected health information (identifiable patient data). P4 data is excluded. Only P3 data is cataloged.
- Customize license terms.
- Provide customization of support of any kind. All datasets are licensed "as is."
Applicants can apply by downloading, signing, and forwarding the standard form license/questionnaire below to [email protected]. Innovation Ventures and the Committee on Enterprise Information and Analytics (EIA) will review the application.
IV Data License / Questionnaire
For questions regarding the archive please get in touch with Ben Olsen at [email protected]. For parties that require data or license customization, don't hesitate to get in touch with [email protected].
*Subscription fees are distributed according to UCSF’s copyright income distribution policy. 70% of subscription fees are returned directly to the originating lab to support future research; 15% is returned to the originating department/school and 15% is retained by the Office of Technology Management and Advancement to fund delivery and maintenance of this archive.
Cataloge of Datasets
Field
Data Composition
Lead Investigator
1) Oncology
Breast Cancer Images – SF2023-XXX: 1000 breast cancer images (500 lymph node positive and 500 lymph node negative) with de-identifying pathology (i.e. pathology reports or parts of the reports).
Zoltan Laszik