Uncertainty Quantification (UQ) studies allow us to determine whether a model is fit for a particular purpose, as well as the operational domain in which it can be used. Standardising the UQ analysis setup and result summary enables the iterative composition of UQ information, which is a crucial step in evaluating model credibility. In this paper, we present an initial attempt to specify UQ information as a cross-layer standard for Modelica-, FMI-, and SSP-based workflows subject to two essential restrictions: (a) uncertainties can only be described in terms of parameters, and (b) analysis is limited to forward uncertainty propagation and sensitivity analysis of nonlinear models. More analysis features are planned for the future. The approach is illustrated using both a simple example and an industrial use case.