In July 2013, the Becker Medical Library at Washington University in St. Louis held a workshop for librarians on the Becker Model, a framework developed by research assessment librarians for quantifying medical researchers' individual and group outputs. Following the workshop, the Becker Model was analyzed for content to adapt it to the physical sciences. This poster presents the process and results of applying their model to the curriculum vitae of a Yale University astronomy professor. ABSTRACT • Examine commonalities and differences between medical and physical sciences fields regarding research impact. • Review literature on scholarly assessment in astronomy to determine the types of assessment that matter. • Apply the Becker Model to citation data and ancillary CV data of an astronomy faculty member at the institution as a proof-of-concept for adapting the Model. • Create a program for research impact workshops to address a diverse physical, life, and social sciences clientele. OBJECTIVES Borne, K. (2001). Data mining in astronomical databases. Mining the Sky, 671–673. doi: 10.1007/10849171_88 Bornmann, L., & Daniel, H. (2009). The state of h index research: Is the h index an ideal way to measure research performance? EMBO Reports, 10(1). doi:10.1038/embor.2008.233 Fortson, L., Masters, K., Nichol, R., Edmondson, E. M., Lintott, C., Raddick, J., Schawinski, K., & Wallin, J. (2012). Galaxy Zoo. In M. J. Way, J. D. Scargle, K. M. Ali, & A. N. Srivastava (Eds.), Advances in Machine Learning and Data Mining for Astronomy (pp. 213–236). Boca Raton, FL: CRC Press. doi:10.1201/b11822-16 Garfield, E. (1979). Is citation analysis a legitimate evaluation tool? Scientometrics, 1(4), 359–375. doi:10.1007/BF02019306 Ginsparg, P. (2011). ArXiv at 20. Nature, 476(7359), 145–7. doi10.1038/476145a Harley, D., Acord, S. K., Earl-Novell, S., Lawrence, S., & King, C. J. (2010). Assessing the future landscape of scholarly communication: An exploration of faculty values and needs in seven disciplines. Berkeley, CA. Retrieved from https://escholarship.org/uc/item/15x7385g.pdf Havemann, F., & Larsen, B. (2014). Bibliometric Indicators of Young Authors in Astrophysics: Can Later Stars be Predicted? arXiv Preprint, 1–14. arXiv:1404.3084 Hourclé, J. A. (2012). Advancing the practice of data citation : A to-do list. Bulletin of the American Society for Information Science and Technology, 38(5), 20–22. Retrieved from http://www.asis.org/Bulletin/Jun-12/ JunJul12_Hourcle.pdf Jamali, H. R., & Nicholas, D. (2009). E-print depositing behavior of physicists and astronomers: An intradisciplinary study. The Journal of Academic Librarianship, 35(2), 117–125. doi:10.1016/j.acalib.2009.01.005 Kousha, K., Thelwall, M., & Rezaie, S. (2010). Can the impact of scholarly images be assessed online? An exploratory study using image identification technology. Journal of the American Society for Information Science and Technology, 61(9), 1734–1744. doi:10.1002/asi.21370 Larivière, V., Sugimoto, C. R., Macaluso, B., Milojević, S., Cronin, B., & Thelwall, M. (2014). arXiv E-prints and the journal of record: An analysis of roles and relationships. Journal of the Association for Information Science and Technology, 65(6), 1157–1169. doi:10.1002/asi.23044 Lawrence, B., Jones, C., Matthews, B., Pepler, S., & Callaghan, S. (2011). Citation and peer review of data: moving towards formal data publication. The International Journal of Digital Curation, 6(2), 4–37. Lozano, G., Larivière, V., & Gingras, Y. (2012). The weakening relationship between the Impact Factor and papers’ citations in the digital age. arXiv Preprint, 2140–2145. doi:10.1002/asi Penfield, T., Baker, M. J., Scoble, R., & Wykes, M. C. (2013). Assessment, evaluations, and definitions of research impact: A review. Research Evaluation, 23(October 2013), 21–32. doi:10.1093/reseval/rvt021 Pepe, A., & Kurtz, M. J. (2012). A measure of total research impact independent of time and discipline. PloS One, 7(11), e46428. do