|DATE:||December 8, 2016|
|TIME:||1:30 - 2:50 pm|
|LOCATION:||Medical School Office Building, Rm x303|
|TITLE:||The Center for Expanded Data Annotation and Retrieval: Making Data "FAIR"
Mark A. Musen, M.D., Ph.D.
In the past couple of years, there has been considerable buzz about making the data sets created through publicly funded investigation findable, accessible, interoperable, and reusable (FAIR). The FAIR principles increasingly guide policy at the NIH and at other federal agencies, although the scientific community is still struggling to identify a means to measure FAIRness. At Stanford, we are leading the Center for Expanded Data Annotation and Retrieval (CEDAR), a center of excellence in the NIH Big Data to Knowledge Program, which has the goal of enhancing the authoring of experimental metadata to make online data sets more FAIR. In this talk, I will discuss the FAIR principles, and the ways in which CEDAR may ease access to and reuse of biomedical data sets stored in public repositories.
Musen, M.A., Bean, C.A., Cheung, K.-H., et al. The Center for Expanded Data Annotation and Retrieval. Journal of the American Medical Informatics Association 22(6):1148–52, 2015. doi:10.1093/jamia/ocv048.
Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J., et al. The FAIR guiding principles for scientific data management and stewardship. Scientific Data 3:160018, 2016. doi: 10.1038/sdata.2016.18