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THE TRAINING OF NEXT GENERATION DATA SCIENTISTS IN BIOMEDICINE
Lana X Garmire1, Stephen Gliske, Quynh C Nguyen
12Epidemiology Program, University of Hawaii Cancer Center,Honolulu, HI, 96813, USA†Work partially supported by grant NIH Big Data 2 Knowledge Award K01ES025434 (to LXG), K01ES026839 (to SG), K01ES025433 (to QCN), K01ES026837 (to JHC), K01ES025445 (to SN), U24 ES026465 (to JDV), by the National Institute of Environmental Health Sciences through funds provided by the trans-NIH Big Data to Knowledge (BD2K) initiative,*work is also partially supported by P20 COBRE GM103457 awarded by NIH/NIGMS, NICHD R01 HD084633, NLM R01 LM012373, and Hawaii Community Foundation Medical Research Grant 14ADVC-64566., LGarmire@Hawaii.edu.
Abstract:
With the booming of new technologies, biomedical science has transformed into digitalized, data intensive science. Massive amount of data need to be analyzed and interpreted, demand a complete pipeline to train next generation data scientists. To meet this need, the transinstitutional Big Data to Knowledge (BD2K) Initiative has been implemented since 2014, complementing other NIH institutional efforts. In this report, we give an overview the BD2K K01 mentored scientist career awards, which have demonstrated early success. We address the specific trainings needed in representative data science areas, in order to make the next generation of data scientists in biomedicine.
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