Abstract
NIH's Clinical and Translational Science Award (CTSA) program represents the National Institutes of Health (NIH) largest single investment in clinical research, as well as one of the world's largest programs in clinical and translational sciences [1]. Although there exist multiple databases and tools to assist NIH program staffs in assessing the program, this work is focused on exploring the image of the program from publically available data sources. In this study, we address both the limitation of linking multiple data elements including CTSA awards and published scientific work, and the challenge of applying advanced data analytic methods to quantitatively evaluate complex NIH programs, considering the CTSA program as an example. We studied multiple dimensions of publications including time, journal, institute and funding; extracted prevailing research topics and productive researchers supported by the program; applied graph analytics to study collaborations of the CTSA program with other funding agencies, and collaborations within the CTSA program.