Exploring the potential transformation of urban data platforms, the study delves into the advancements of User Interfaces (UIs), particularly focusing on personalized and adaptive UIs within the smart city landscape. Recognizing the complexities arising from domain-specific or overly broad urban data platforms, the research navigates through the evolutionary trajectory of UIs in urban settings. Introducing the concept of Self-Adaptive User Interfaces (SAUIs), the study emphasizes their dynamic responsiveness to user needs based on contextual data. Through a synthesis of design, models, and data-driven insights, the integration of generative design patterns and model-driven development lays the foundation for culturally sensitive and context-aware UIs. The paper showcases a prototype implementation of an urban data platform and outlines the design concept for the prospective implementation of SAUI. Prospective research endeavors aim to assess these interfaces in real-world scenarios and explore alternative UI design approaches for optimal integration into smart cities.