Existing tools for scientific modeling offer little support for improving models in response to data, whereas computational methods for scientific knowledge discovery provide few opportunities for user input. In this paper, we present a language for stating process models and background knowledge in terms familiar to scientists, along with an interactive environment for knowledge discovery that lets the user construct, edit, and visualize scientific models, use them to make predictions, and revise them to better fit available data. We report initial studies in three domains that illustrate the operation of this environment and the results of a user study carried out with domain scientists. Finally, we discuss related efforts on model formalisms and revision and suggest priorities for additional research.