Principal Investigator/Program Director: John Kwagyan, PhD Project Summary Advances in technologies and computational tools has made it possible to generate and store large, complex, and diverse datasets. The behavioral, biomedical and health research enterprise is increasingly becoming data- intensive and data-driven. As a result, recognizing, understanding, and using big data for behavioral, biomedical, and health related research have become necessary to arrive at best evidence and enhance translation. Applied data science starts with identifying relevant data sources, developing algorithms and/or utilization of existing software tools to access these data and employing advanced data analytical skills for knowledge discovery and dissemination of information. The methodology is highly developed and is utilized in various areas of research, insurance, business, and healthcare. In biomedical and healthcare areas, big data methodology is used in several fields including but not limited to medical imaging studies, drug discovery, genomics, predictive diagnosis and cost effectiveness studies. Data science also allows researchers to assess patient/population heterogeneity, through the integration of large data from published literature and meta-analysis to reach conclusions that can be used to inform clinical practice and guide public health policy. Skill sets in data science are also particularly critical for advancing the science of minority health and health disparities. Despite the importance of the emerging field of data science and the recent rapid rise of its use, many minority-serving institutions do not offer specialized training in data science. Moreover, though the approach is highly developed, there are few who possess the necessary skill set in this highly quantitative and technical field and training opportunities are uncommon. Additionally, there exist disparities in data science expertise and training opportunities in minority-serving institutions. The two major goals of this application are therefore to (i) enhance capacity building in data science by offering a comprehensive training series that engages new and established researchers of various disciplines, and (ii) foster collaboration in data science research among researchers in RCMIs and other minority-serving institutions. The goals will be accomplished through the creation of the Virtual Applied Data Science Training Institute, VADSTI. The proposed VADSTI, will draw faculty with complementary expertise in the conduct and application of data science from multiple institutions as well as partner with the NIH Office of Data Science Strategy to launch an 8-week comprehensive training in a virtual (online) environment. The objective is to address and close the gap in disparities in knowledge, understanding and application of data science in RCMI institutions and other minority-serving institutions. PHS 398 (Rev. 01/18 Approved Through 03/31/2020) Page 1 OMB No. 0925-0001
Kwagyan, John. Project Narrative Despite the importance of the emerging field of data science and the recent rapid rise of its use, many minority institutions do not offer specialized training in this highly quantitative and technical field, and there exist disparities in data science expertise in minority-serving institutions. Skill sets in data science are also particularly critical for advancing the science of minority health and health disparities, however, the ability of behavioral, biomedical and clinical researchers to recognize, and use big data is often limited for various reasons including lack of exposure to relevant databases and knowledge of programming techniques and access to relevant software, tools, and expertise in data analytics. The significance of this proposal is to showcase the importance of data science and attract and engage underrepresented researchers in its application to biomedical, behavioral and clinical research, with a focus on diseases common to minority populations. PHS 398/2590 (Rev. 09/04, Reissued 4/2006) Page 1 Continuation Format Page
