"Research is becoming increasingly data intensive and computation driven across various scientific domains from the social and life sciences all the way to particle physics. Many new scientific insights will likely emerge from vast stores of existing data, rather than from new data collection efforts. In addition, funder and journal mandates now require that researchers share at least the final datasets at the time of publication.

rOpenSci is an effort to foster such data driven science among researchers that use R. Our suite of tools
(http://ropensci.org/packages/) allow access to these data repositories through a statistical programming environment that is already a familiar part of the workflow of many scientists. Our tools not only facilitate drawing data into an environment where it can readily be manipulated, but also one in which those analyses and methods can be easily shared, replicated, and extended by other researchers. In this talk we highlight some our recent efforts in advancing open and transparent practices in the sciences."