Ensuring semantic consistency and data integrity of information exchanges between these interconnected systems requires robust information and data models. As new models are emerging, it is essential to evaluate them during the design process. However, model developers often lack clear methods or guidelines for evaluating their new information and data models. We conduct a narrative literature review of academic publications to understand the current state. We generate a simple visual illustration mapping our focus in the context of information and data model evaluation with existing approaches to assist model developers in identifying suitable methods. Our findings highlight two main approaches for information models, while also identifying a gap in evaluation approaches for data models. Future work could focus on designing a combined approach for IMs & DMs to provide a structured guidance for model developers.