Figure 1 from: Eitzel M.V (2021) A modeler's manifesto: Synthesizing modeling best practices with social science frameworks to support critical approaches to data science. Research Ideas and Outcomes 7: e71553. https://doi.org/10.3897/rio.7.e71553

Figure 1 Workflow diagram for manifesto practices, showing which project stages may benefit from which practices. Interdisciplinary fluency, engaging with community-based modeling, and paying attention to power dynamics as well as impacts and implications are all important at all stages of modeling work. Epistemic consistency is important throughout model development (the three middle steps of model choice, construction, and description) and communication, while triangulation and mixed methods contribute largely to model development. The data biography is most important in the model description stage, though one may need to keep a journal and track details of the model development process in order to create the data biography. Treating uncertainty as openness is most important in model communication and application; however, this could feed back into iterative model development steps as well, or one could design models to aid in treating uncertainty as openness.