Data science is a team sport. A wide variety of skills are needed to extract knowledge from data. Although those skills are often grouped into “computing” and “statistical analysis,” these are very general terms and, depending on the problem, very specialized knowledge within those areas may be necessary. The variety of specialized knowledge is seldom found in one person. Apply data science to biomedical science and even fewer people have both knowledge backgrounds. Therefore, in order to do biomedical data science, more often than not, a team is needed.
The Big Data to Knowledge (BD2K) program supports efforts to build biomedical data science teams. One such effort is an Innovation Lab, which kicks off next week. This is a week-long workshop for junior faculty from the biomedical sciences and the data sciences. Under the guidance of mentors (senior investigators in their fields), the participants form teams and refine their research programs.
Another effort to build biomedical data science teams is the Data Science Rotations for Advancing Discovery (Data Science RoAD-Trip), developed by the BD2K Training Coordinating Center (TCC). The RoAD-Trip program matches junior-level biomedical investigators with more senior data scientists to collaborate on a biomedical data science research project. The biomedical scientists bring compelling pre-existing biomedical data and problems, while the data scientists bring analytical skills and resources. After individuals apply, the TCC will suggest matches between biomedical scientists and data scientists, and will invite joint applications from paired groups.
The program is entitled RoAD-Trip because selected junior investigators will “take to the road” and collaborate with senior data science mentors at another research institution. The TCC will reimburse travel expenses and give an honorarium. To learn more about the Data Science RoAD-Trip, see: www.bigdatau.org/roadtrip. The application deadline is September 2, 2016. Please direct questions to firstname.lastname@example.org.