Efforts to implement FAIR (Findable, Accessible, Interoperable, and Reusable) data principles are becoming widespread in the sciences thanks to both published and evangelistic dissemination of FAIR best practices. Infrastructure to accommodate FAIR guiding principles often exists in terms of findability and accessibility; however, systems that facilitate interoperability and reusability aspects may be more difficult to implement for multi-sector, multi-scale research projects. This is largely due to 1) the lack of provenance inheritance from participating models, 2) the loss and miscommunication of “conversion” libraries in forcing and coupling experiments, 3) multiple programming language use specifications for data types, and 4) lacking requirements for metadata and runtime logging for contributing models. In this work, we present an approach that specifically addresses the “Reusable” component of FAIR from a preemptive design perspective of a multi-model integrated ecosystem. The GCAM ecosystem of models encompasses data development, single-system, statistical emulator, and disaggregation models around an integrated human-Earth systems model where each participating model is designed to produce richly described, open-source licensed, provenance documented, community standardized data. Paying consideration to FAIR principles at the time of model development, especially in integrated modeling environments, sets the stage for success in the sustainability of research data.