Data driven science and research provides an avenue to accurately model complex bio-social systems. The ability to model these systems helps us to identify key actors, critical events, and make predictions about future pathways/trajectories of the micro-components and macro-behaviors. Applying a data driven approach to a specific case of innovation in biomedicine, the microbiome concept, allows us to analyze factors which drive biomedical innovation. Building on the products and results of this case study we are developing data products, workflows, and architecture for others to implement data-driven science and research frameworks into their own research projects.