Living DAGs: the future of DAGs in epidemiology

Directed acyclic graphs (DAGs) are now standard tools for selecting covariates and identifying estimands in causal inference. Yet in most applications, DAGs are treated as static and study-specific and then discarded rather than maintained as cumulative infrastructure. This opinion piece argues that DAGs can serve a much broader role: as epistemic infrastructure that supports cumulative science. By treating DAGs as living, shared representations of causal systems-annotated with levels of evidence, revised over time, and tested empirically-we enable a mode of scientific practice that is transparent, collaborative, and intervention-oriented. Examples from spaceflight risk management and cerebral palsy research demonstrate how DAGs are already being used this way. I call on the field of epidemiology to adopt this approach more broadly: to share, refine, and re-use DAGs not just as tools of analysis, but as frameworks for designing better questions and building a more cumulative science.