UCSF’s Information Commons...
Harnessing the power of machine intelligence to advance precision medicine.

What is Information Commons?

Information Commons is a fast and easily searchable and accessible repository of all UCSF clinical data and models, and related basic science & population data, that enables UCSF research and discovery of new health insights underlying precision medicine, to improve patient and health care.


Information Commons hosts multi-factor and multi-modal data, including UCSF’s structured clinical data, clinical notes, meta-data on clinical notes, extracted concepts from clinical notes using Natural Language Processing (NLP) and other approaches, radiological images, meta-data extracted from DICOM (DigitalImaging and Communications in Medicine) headers.

Learn about the Data


Best of breed tools, including UC Berkeley-developed Spark computing paradigm, employing a “compute to the data” model for Very Large data mining and pattern discovery, clinical Text Analysis Knowledge Extraction System (cTAKES), imaging exploration (a.k.a. Imaging Commons), machine learning models, and user friendly interactive interfaces for patient cohort exploration have been implemented.

Learn about the Tools


High performance compute infrastructure, including on the cloud hosting with AWS leveraging powerful compute capabilities such as Elastic Map Reduce, and on premise hosting on UCSF’s Wynton computing cluster. 



Learn about the Infrastructure



Information Commons is currently in beta.  For a full list of features, and how to gain early access, see our wiki.

If you are a UCSF researcher with a computational project, Information Commons can offer a number of options to suit your research needs. 

See our Wiki


Information Commons specializes in supporting integrative research.  Clinical data, doctors’ notes, radiology images, specialist and lab reports – all are used in multifactor studies, with many more forms to come.


See our Featured Research