I am increasingly asked to describe the difference between data science and biomedical informatics. Distinguishing these disciplines takes on added importance with the recent publication of the NIH Advisory Committee to the Director, National Library of Medicine (NLM) Working Group, report on the future of the NLM, which calls for NLM to become a leader in data science at NIH. NLM has of course historically been a leader in research and training in biomedical informatics.
What is, if any, the difference between informatics and data science? Let me start with definitions. I have written my own definitions of biomedical informatics [1] but for the sake of the community, let me quote the latest consensus definition from our professional association, the American Medical Informatics Association (AMIA) [2]: “Biomedical informatics (BMI) is the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health.”
